Contributor: Ministerstvo školství, mládeže a tělovýchovy České republiky@@LM2018101@@LINDAT/CLARIAH-CZ: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy@@nationalFunds@@

Start Over Contributor Ministerstvo školství, mládeže a tělovýchovy České republiky@@LM2018101@@LINDAT/CLARIAH-CZ: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy@@nationalFunds@@

1. A Human-Annotated Dataset for Language Modeling and Named Entity Recognition in Medieval Documents

Creator:: Novotný, Vít, Luger, Kristýna, Štefánik, Michal, Vrabcová, Tereza, and Horák, Aleš
Publisher:: Masaryk University, Brno
Type:: text and corpus
Subject:: NER, named entity recognition, and Medieval
Language:: Czech, English, German, and Latin
Description:: This is an open dataset of sentences from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains a corpus for language modeling and human annotations for named entity recognition (NER).
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

2. A Human-Annotated Dataset for Language Modeling and Named Entity Recognition in Medieval Documents (2023-01-05)

Creator:: Novotný, Vít, Luger, Kristýna, Štefánik, Michal, Vrabcová, Tereza, and Horák, Aleš
Publisher:: Masaryk University, Brno
Type:: text and corpus
Subject:: NER, named entity recognition, and Medieval
Language:: Czech, English, German, and Latin
Description:: This is an open dataset of sentences from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains a corpus for language modeling and human annotations for named entity recognition (NER).
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

3. A Human-Annotated Dataset of Scanned Images and OCR Texts from Medieval Documents

Creator:: Novotný, Vít, Seidlová, Kristýna, Vrabcová, Tereza, and Horák, Aleš
Publisher:: Masaryk University, Brno
Type:: image and corpus
Subject:: ocr, optical character recognition, language identification, image super-resolution, sr, and Medieval
Language:: German, Czech, Latin, and English
Description:: This is an open dataset of scanned images and OCR texts from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains human annotations for layout analysis, OCR evaluation, and language identification.
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

4. A Human-Annotated Dataset of Scanned Images and OCR Texts from Medieval Documents: Supplementary Materials

Creator:: Novotný, Vít and Horák, Aleš
Publisher:: Masaryk University, Brno
Type:: text and corpus
Subject:: ocr, optical character recognition, language identification, image super-resolution, sr, and Medieval
Language:: Czech, English, German, and Latin
Description:: These are supplementary materials for an open dataset of scanned images and OCR texts from 19th and 20th century letterpress reprints of documents from the Hussite era. The dataset contains human annotations for layout analysis, OCR evaluation, and language identification and is available at http://hdl.handle.net/11234/1-4615. These supplementary materials contain OCR texts from different OCR engines for book pages for which we have both high-resolution scanned images and annotations for OCR evaluation.
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

5. Annotate

Creator:: Roček, Martin
Publisher:: Charles University, Faculty of Arts
Type:: TEXT and toolService
Subject:: manuscripts, annotation, application, TEI, and JavaScript
Language:: No linguistic content
Description:: Annotate is a web and desktop application that should simplify the process of transforming photos of manuscripts to a browsable collection. It also allows users to annotate parts of the displayed images.
Rights:: GNU Library or "Lesser" General Public License 3.0 (LGPL-3.0), http://opensource.org/licenses/LGPL-3.0, and PUB

6. Bosworth-Toller’s Anglo-Saxon Dictionary online

Creator:: Tichý, Ondřej, Roček, Martin, Bočková, Renata, Čermák, Matěj, Dragounová, Jolana, Filipová, Helena, Gilová, Lucie, Hejná, Michaela, Hladíková, Lenka, Hladká, Alena, Hubinová, Veronika, Krajcsovicsová, Vlaďena, Kupková, Tatiana, Lebedeva, Tatiana, Malečková, Nikola, Novotná, Alena, Pazderová, Tereza, Popelíková, Jiřina, Rumlová, Jana, Tyčová Ocelík, Dana, Volná, Veronika, and Zahradníková, Tereza
Publisher:: Charles University, Faculty of Arts, Department of English Language and ELT Methodology
Type:: text, lexicon, and lexicalConceptualResource
Subject:: English, Old English, Anglo-Saxon, dictionary, Bosworth, Toller, lexicography, digitalization, English history, Mediaeval, and Medieval
Language:: English, Old English (ca. 450-1100), Latin, Ancient Greek (to 1453), and Ancient Hebrew
Description:: Description : This is an online edition of An Anglo-Saxon Dictionary, or a dictionary of "Old English". The dictionary records the state of the English language as it was used between ca. 700-1100 AD by the Anglo-Saxon inhabitants of the British Isles. This project is based on a digital edition of An Anglo-Saxon dictionary, based on the manuscript collections of the late Joseph Bosworth (the so called Main Volume, first edition 1898) and its Supplement (first edition 1921), edited by Joseph Bosworth and T. Northcote Toller, today the largest complete dictionary of Old English (one day to be hopefully supplanted by the DOE). Alistair Campbell's "enlarged addenda and corrigenda" from 1972 are not public domain and are therefore not part of the online dictionary. Please see the front & back matter of the paper dictionary for further information, prefaces and lists of references & contractions. The digitization project was initiated by Sean Crist in 2001 as a part of his Germanic Lexicon Project and many individuals and institutions have contributed to this project. Check out the original GLP webpage and the old Bosworth-Toller offline application webpage (to be updated). Currently the project is hosted by the Faculty of Arts, Charles University. In 2010, the data from the GLP were converted to create the current site. Care was taken to preserve the typography of the original dictionary, but also provide a modern, user friendly interface for contemporary users. In 2013, the entries were structurally re-tagged and the original typography was abandoned, though the immediate access to the scans of the paper dictionary was preserved. Our aim is to reach beyond a simple digital edition and create an online environment dedicated to all interested in Old English and Anglo-Saxon culture. Feel free to join in the editing of the Dictionary, commenting on its numerous entries or participating in the discussions at our forums. We hope that by drawing the attention of the community of Anglo-Saxonists to our site and joining our resources, we may create a more useful tool for everybody. The most immediate project to draw on the corrected and tagged data of the Dictionary is a Morphological Analyzer of Old English (currently under development). We are grateful for the generous support of the Charles University Grant Agency and for the free hosting at the Faculty of Arts at Charles University. The site is currently maintained and developed by Ondrej Tichy et al. at the Department of English Language and ELT Methodology, Faculty of Arts, Charles University in Prague (Czech Republic).
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

7. CoCzeFLA Chroma 2022.07

Creator:: Chromá, Anna and Matiasovitsová, Klára
Publisher:: Faculty of Arts, Charles Univesity
Type:: text and corpus
Subject:: first language acquisition, typical development, and monolingual corpus
Language:: Czech
Description:: Transcripts of longitudinal audio recordings of 7 Czech typical monolingual children between 1;7 to 3;9. Files are in plain text with UTF-8 encoding. Each file represents one recording session of one of the target children and is named with the presudonym of the child and her age at the given session in form YMMDD. Transcription rules and other details are to find on the homepage coczefla.ff.cuni.cz.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

8. CoCzeFLA Chroma 2023.04

Creator:: Chromá, Anna, Matiasovitsová, Klára, Sláma, Jakub, and Treichelová, Jolana
Publisher:: Charles University, Faculty of Arts
Type:: text and corpus
Subject:: first language acquisition, typical development, longitudinal corpus, and Czech
Language:: Czech
Description:: A new version of the previously published corpus Chroma. The version 2023.04 includes six children. Two transcripts (Julie20221, Klara30424) were removed since they did not meet the criteria on the dialogical format. The transcripts were revised (eliminating typing errors and inconsistencies in the transcription format) and morphologically annotated by the automatic tool MorphoDiTa. Detailed manual control of the annotation was performed on children's utterances; the annotation of adult data was not checked yet. Files are in plain text with UTF-8 encoding. Each file represents one recording session of one of the target children and is named with the alias of the child and their age at the given session in form YMMDD. Transcription rules and other details can be found on the homepage coczefla.ff.cuni.cz.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

9. CoCzeFLA Chroma 2023.07

Creator:: Chromá, Anna, Sláma, Jakub, Matiasovitsová, Klára, and Kohoutková, Jolana
Publisher:: Charles University, Faculty of Arts
Type:: text and corpus
Subject:: first language acquisition, typical development, longitudinal corpus, and Czech
Language:: Czech
Description:: A new version of the previously published corpus Chroma wih morphological annotation. The version 2023.07 differs from 2023.04 in that it includes all seven children and it went through an additional careful check of consistency and conformity to the CHAT transcription principles. Two transcripts (Julie20221, Klara30424) from the previous versions (2022.07, 2019.07) were removed since they did not meet our criteria on dialogical format. All transcripts of recordings made during one day were split into one file. Thus, version 2023.07 consists of 183 files/transcripts. The number of utterances and tokens given here in LINDAT corresponds to children's lines only. Files are in plain text with UTF-8 encoding. Each file represents one recording session of one of the target children and is named with the alias of the child and their age at the given session in form YMMDD. Transcription rules and other details can be found on the homepage coczefla.ff.cuni.cz.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

10. CoNLL-based Extended Czech Named Entity Corpus 1.0

Creator:: Konkol, Michal, Konopík, Miloslav, Ševčíková, Magda, Žabokrtský, Zdeněk, and Straková, Jana
Publisher:: University of West Bohemia
Type:: text and corpus
Subject:: named entity recognition, Czech, and conll
Language:: Czech
Description:: This is a Czech Named Entity Corpus 1.0 transformed into the CoNLL format. The original corpus can be downloaded from: http://hdl.handle.net/11858/00-097C-0000-0023-1B04-C. The CoNLL transformation is described in this publication: https://link.springer.com/chapter/10.1007/978-3-642-40585-3_20.
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

11. CoNLL-based Extended Czech Named Entity Corpus 2.0

Creator:: Konkol, Michal, Konopík, Miloslav, Ševčíková, Magda, Žabokrtský, Zdeněk, Straková, Jana, and Straka, Milan
Publisher:: University of West Bohemia
Type:: text and corpus
Subject:: named entity recognition and Czech
Language:: Czech
Description:: This is a Czech Named Entity Corpus 2.0 transformed into the CoNLL format. The original corpus can be downloaded from: http://hdl.handle.net/11858/00-097C-0000-0023-1B22-8. The CoNLL transformation is described in this publication: https://link.springer.com/chapter/10.1007/978-3-642-40585-3_20.
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

12. Coreference in Universal Dependencies 0.1 (CorefUD 0.1)

Creator:: Nedoluzhko, Anna, Novák, Michal, Popel, Martin, Žabokrtský, Zdeněk, and Zeman, Daniel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: dependency, treebank, coreference, bridging relations, and harmonized annotation
Language:: Catalan, Czech, Dutch, English, French, German, Hungarian, Lithuanian, Polish, Russian, and Spanish
Description:: CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 0.1 consists of 17 datasets for 11 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 13 datasets for 10 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 1 for Hungarian, 1 for Lithuanian, 1 for Polish, 1 for Russian, and 1 for Spanish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. References to original resources whose harmonized versions are contained in the public edition of CorefUD 0.1: - Catalan-AnCora: Recasens, M. and Martí, M. A. (2010). AnCora-CO: Coreferentially Annotated Corpora for Spanish and Catalan. Language Resources and Evaluation, 44(4):315–345 - Czech-PCEDT: Nedoluzhko, A., Novák, M., Cinková, S., Mikulová, M., and Mírovský, J. (2016). Coreference in Prague Czech-English Dependency Treebank. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 169–176, Portorož, Slovenia. European Language Resources Association. - Czech-PDT: Hajič, J., Bejček, E., Hlaváčová, J., Mikulová, M., Straka, M., Štěpánek, J., and Štěpánková, B. (2020). Prague Dependency Treebank - Consolidated 1.0. In Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020), pages 5208–5218, Marseille, France. European Language Resources Association. - English-GUM: Zeldes, A. (2017). The GUM Corpus: Creating Multilayer Resources in the Classroom. Language Resources and Evaluation, 51(3):581–612. - English-ParCorFull: Lapshinova-Koltunski, E., Hardmeier, C., and Krielke, P. (2018). ParCorFull: a Parallel Corpus Annotated with Full Coreference. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan. European Language Resources Association. - French-Democrat: Landragin, F. (2016). Description, modélisation et détection automatique des chaı̂nes de référence (DEMOCRAT). Bulletin de l’Association Française pour l’Intelligence Artificielle, (92):11–15. - German-ParCorFull: Lapshinova-Koltunski, E., Hardmeier, C., and Krielke, P. (2018). ParCorFull: a Parallel Corpus Annotated with Full Coreference. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan. European Language Resources Association - German-PotsdamCC: Bourgonje, P. and Stede, M. (2020). The Potsdam Commentary Corpus 2.2: Extending annotations for shallow discourse parsing. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 1061–1066, Marseille, France. European Language Resources Association. - Hungarian-SzegedKoref: Vincze, V., Hegedűs, K., Sliz-Nagy, A., and Farkas, R. (2018). SzegedKoref: A Hungarian Coreference Corpus. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan. European Language Resources Association. - Lithuanian-LCC: Žitkus, V. and Butkienė, R. (2018). Coreference Annotation Scheme and Corpus for Lithuanian Language. In Fifth International Conference on Social Networks Analysis, Management and Security, SNAMS 2018, Valencia, Spain, October 15-18, 2018, pages 243–250. IEEE. - Polish-PCC: Ogrodniczuk, M., Glowińska, K., Kopeć, M., Savary, A., and Zawisławska, M. (2013). Polish coreference corpus. In Human Language Technology. Challenges for Computer Science and Linguistics - 6th Language and Technology Conference, LTC 2013, Poznań, Poland, December 7-9, 2013. Revised Selected Papers, volume 9561 of Lecture Notes in Computer Science, pages 215–226. Springer. - Russian-RuCor: Toldova, S., Roytberg, A., Ladygina, A. A., Vasilyeva, M. D., Azerkovich, I. L., Kurzukov,M., Sim, G., Gorshkov, D. V., Ivanova, A., Nedoluzhko, A., and Grishina, Y. (2014). Evaluating Anaphora and Coreference Resolution for Russian. In Komp’juternaja lingvistika i intellektual’nye tehnologii. Po materialam ezhegodnoj Mezhdunarodnoj konferencii Dialog, pages 681–695. - Spanish-AnCora: Recasens, M. and Martí, M. A. (2010). AnCora-CO: Coreferentially Annotated Corpora for Spanish and Catalan. Language Resources and Evaluation, 44(4):315–345 References to original resources whose harmonized versions are contained in the ÚFAL-internal edition of CorefUD 0.1: - Dutch-COREA: Hendrickx, I., Bouma, G., Coppens, F., Daelemans, W., Hoste, V., Kloosterman, G., Mineur, A.-M., Van Der Vloet, J., and Verschelde, J.-L. (2008). A coreference corpus and resolution system for Dutch. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08), Marrakech, Morocco. European Language Resources Association. - English-ARRAU: Uryupina, O., Artstein, R., Bristot, A., Cavicchio, F., Delogu, F., Rodriguez, K. J., and Poesio, M. (2020). Annotating a broad range of anaphoric phenomena, in a variety of genres: the ARRAU Corpus. Natural Language Engineering, 26(1):95–128. - English-OntoNotes: Weischedel, R., Hovy, E., Marcus, M., Palmer, M., Belvin, R., Pradhan, S., Ramshaw, L., and Xue, N. (2011). Ontonotes: A large training corpus for enhanced processing. In Handbook of Natural Language Processing and Machine Translation: DARPA Global Autonomous Language Exploitation, pages 54–63, New York. Springer-Verlag. - English-PCEDT: Nedoluzhko, A., Novák, M., Cinková, S., Mikulová, M., and Mírovský, J. (2016). Coreference in Prague Czech-English Dependency Treebank. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 169–176, Portorož, Slovenia. European Language Resources Association.
Rights:: Licence CorefUD v0.1, https://lindat.mff.cuni.cz/repository/xmlui/page/license-corefud-0.1, and PUB

13. Coreference in Universal Dependencies 0.2 (CorefUD 0.2)

Creator:: Nedoluzhko, Anna, Novák, Michal, Popel, Martin, Žabokrtský, Zdeněk, and Zeman, Daniel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: dependency, treebank, coreference, bridging relations, and harmonized annotation
Language:: Catalan, Czech, Dutch, English, French, German, Hungarian, Lithuanian, Polish, Russian, and Spanish
Description:: CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 0.2 consists of 17 datasets for 11 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 13 datasets for 10 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 1 for Hungarian, 1 for Lithuanian, 1 for Polish, 1 for Russian, and 1 for Spanish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. Version 0.2 consists of exactly the same datasets as the version 0.1. All automatically parsed datasets were re-parsed for v0.2 using UDPipe 2 with models trained on UD 2.6. Catalan-AnCora, Spanish-AnCora and English-GUM have been updated to match the their UD 2.9 versions.
Rights:: Licence CorefUD v0.2, https://lindat.mff.cuni.cz/repository/xmlui/page/license-corefud-0.2, and PUB

14. Coreference in Universal Dependencies 1.0 (CorefUD 1.0)

Creator:: Nedoluzhko, Anna, Novák, Michal, Popel, Martin, Žabokrtský, Zdeněk, Zeldes, Amir, Zeman, Daniel, Bourgonje, Peter, Cinková, Silvie, Hajič, Jan, Hardmeier, Christian, Krielke, Pauline, Landragin, Frédéric, Lapshinova-Koltunski, Ekaterina, Martí, M. Antònia, Mikulová, Marie, Ogrodniczuk, Maciej, Recasens, Marta, Stede, Manfred, Straka, Milan, Toldova, Svetlana, Vincze, Veronika, and Žitkus, Voldemaras
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: dependency, treebank, coreference, bridging relations, and harmonized annotation
Language:: Catalan, Czech, Dutch, English, French, German, Hungarian, Lithuanian, Polish, Russian, and Spanish
Description:: CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 1.0 consists of 17 datasets for 11 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 13 datasets for 10 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 1 for Hungarian, 1 for Lithuanian, 1 for Polish, 1 for Russian, and 1 for Spanish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. Version 1.0 consists of the same corpora and languages as the previous version 0.2; however, the English GUM dataset has been updated to a newer and larger version, and in the Czech/English PCEDT dataset, the train-dev-test split has been changed to be compatible with OntoNotes. Nevertheless, the main change is in the file format (the MISC attributes have new form and interpretation).
Rights:: Licence CorefUD v0.2, https://lindat.mff.cuni.cz/repository/xmlui/page/license-corefud-0.2, and PUB

15. Coreference in Universal Dependencies 1.2 (CorefUD 1.2)

Creator:: Popel, Martin, Novák, Michal, Žabokrtský, Zdeněk, Zeman, Daniel, Nedoluzhko, Anna, Acar, Kutay, Bamman, David, Bourgonje, Peter, Cinková, Silvie, Eckhoff, Hanne, Cebiroğlu Eryiğit, Gülşen, Hajič, Jan, Hardmeier, Christian, Haug, Dag, Jørgensen, Tollef, Kåsen, Andre, Krielke, Pauline, Landragin, Frédéric, Lapshinova-Koltunski, Ekaterina, Mæhlum, Petter, Martí, M. Antònia, Mikulová, Marie, Nøklestad, Anders, Ogrodniczuk, Maciej, Øvrelid, Lilja, Pamay Arslan, Tuğba, Recasens, Marta, Solberg, Per Erik, Stede, Manfred, Straka, Milan, Swanson, Daniel, Toldova, Svetlana, Vadász, Noémi, Velldal, Erik, Vincze, Veronika, Zeldes, Amir, and Žitkus, Voldemaras
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: coreference, bridging relations, harmonized annotation, dependency, and treebank
Language:: Ancient Greek (to 1453), Ancient Hebrew, Catalan, Czech, English, French, German, Hungarian, Lithuanian, Norwegian, Church Slavic, Polish, Russian, Spanish, and Turkish
Description:: CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 1.2 consists of 25 datasets for 16 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 21 datasets for 15 languages (1 dataset for Ancient Greek, 1 for Ancient Hebrew, 1 for Catalan, 2 for Czech, 3 for English, 1 for French, 2 for German, 2 for Hungarian, 1 for Lithuanian, 2 for Norwegian, 1 for Old Church Slavonic, 1 for Polish, 1 for Russian, 1 for Spanish, and 1 for Turkish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource, too. Compared to the previous version 1.1, the version 1.2 comprises new languages and corpora, namely Ancient_Greek-PROIEL, Ancient_Hebrew-PTNK, English-LitBank, and Old_Church_Slavonic-PROIEL. In addition, English-GUM and Turkish-ITCC have been updated to newer versions, conversion of zeros in Polish-PCC has been improved, and the conversion pipelines for multiple other datasets have been refined (a list of all changes in each dataset can be found in the corresponding README file).
Rights:: Licence CorefUD v1.2, https://lindat.mff.cuni.cz/repository/xmlui/page/license-corefud-1.2, and PUB

16. CUBBITT Translation Models (en-cs) (v1.0)

Creator:: Popel, Martin, Tomková, Markéta, Tomek, Jakub, Kaiser, Łukasz, Uszkoreit, Jakob, Bojar, Ondřej, and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: machine translation, neural machine translation, transformer, and cubbitt
Language:: English and Czech
Description:: CUBBITT En-Cs translation models, exported via TensorFlow Serving, available in the Lindat translation service (https://lindat.mff.cuni.cz/services/translation/). Models are compatible with Tensor2tensor version 1.6.6. For details about the model training (data, model hyper-parameters), please contact the archive maintainer. Evaluation on newstest2014 (BLEU): en->cs: 27.6 cs->en: 34.4 (Evaluated using multeval: https://github.com/jhclark/multeval)
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

17. CUBBITT Translation Models (en-fr) (v1.0)

Creator:: Popel, Martin, Tomková, Markéta, Tomek, Jakub, Kaiser, Łukasz, Uszkoreit, Jakob, Bojar, Ondřej, and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: machine translation, neural machine translation, transformer, and cubbitt
Language:: English and French
Description:: CUBBITT En-Fr translation models, exported via TensorFlow Serving, available in the Lindat translation service (https://lindat.mff.cuni.cz/services/translation/). Models are compatible with Tensor2tensor version 1.6.6. For details about the model training (data, model hyper-parameters), please contact the archive maintainer. Evaluation on newstest2014 (BLEU): en->fr: 38.2 fr->en: 36.7 (Evaluated using multeval: https://github.com/jhclark/multeval)
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

18. CUBBITT Translation Models (en-pl) (v1.0)

Creator:: Popel, Martin, Tomková, Markéta, Tomek, Jakub, Kaiser, Łukasz, Uszkoreit, Jakob, Bojar, Ondřej, and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: machine translation, neural machine translation, transformer, and cubbitt
Language:: English and Polish
Description:: CUBBITT En-Pl translation models, exported via TensorFlow Serving, available in the Lindat translation service (https://lindat.mff.cuni.cz/services/translation/). Models are compatible with Tensor2tensor version 1.6.6. For details about the model training (data, model hyper-parameters), please contact the archive maintainer. Evaluation on newstest2020 (BLEU): en->pl: 12.3 pl->en: 20.0 (Evaluated using multeval: https://github.com/jhclark/multeval)
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

19. Czech and English abstracts of ÚFAL papers (2022-11-11)

Creator:: Rosa, Rudolf and Zouhar, Vilém
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: parallel corpus, scientific texts, and abstracts
Language:: Czech and English
Description:: This is a parallel corpus of Czech and mostly English abstracts of scientific papers and presentations published by authors from the Institute of Formal and Applied Linguistics, Charles University in Prague. For each publication record, the authors are obliged to provide both the original abstract (in Czech or English), and its translation (English or Czech) in the internal Biblio system. The data was filtered for duplicates and missing entries, ensuring that every record is bilingual. Additionally, records of published papers which are indexed by SemanticScholar contain the respective link. The dataset was created from September 2022 image of the Biblio database and is stored in JSONL format, with each line corresponding to one record.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

20. Czech Models (MorfFlex CZ 2.0 + PDT-C 1.0) for MorphoDiTa 220710

Creator:: Straka, Milan and Straková, Jana
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, languageDescription, and mlmodel
Subject:: MorphoDiTa, Czech, morphological analysis, morphological generation, and PoS tagging
Language:: Czech
Description:: Czech models for MorphoDiTa, providing morphological analysis, morphological generation and part-of-speech tagging. The morphological dictionary is created from MorfFlex CZ 2.0, DeriNet 2.1 and the PoS tagger is trained on Prague Dependency Treebank - Consolidated 1.0. and This work has been using language resources developed and/or stored and/or distributed by the LINDAT/CLARIN project of the Ministry of Education of the Czech Republic (project LM2010013). The Czech morphologic system was devised by Jan Hajič. The MorfFlex CZ dictionary was created by Jan Hajič and Jaroslava Hlaváčová. The morphologic guesser research was supported by the projects 1ET101120503 and 1ET101120413 of Academy of Sciences of the Czech Republic and 100008/2008 of Charles University Grant Agency. The research was performed by Jan Hajič, Jaroslava Hlaváčová and David Kolovratník. The tagger algorithm and feature set research was supported by the projects MSM0021620838 and LC536 of Ministry of Education, Youth and Sports of the Czech Republic, GA405/09/0278 of the Grant Agency of the Czech Republic and 1ET101120503 of Academy of Sciences of the Czech Republic. The research was performed by Drahomíra "johanka" Spoustová, Jan Hajič, Jan Raab and Miroslav Spousta. The tagger is trained on morphological layer of Prague Dependency Treebank PDT 2.5, which was supported by the projects LM2010013, LC536, LN00A063 and MSM0021620838 of Ministry of Education, Youth and Sports of the Czech Republic, and developed by Martin Buben, Jan Hajič, Jiří Hana, Hana Hanová, Barbora Hladká, Emil Jeřábek, Lenka Kebortová, Kristýna Kupková, Pavel Květoň, Jiří Mírovský, Andrea Pfimpfrová, Jan Štěpánek and Daniel Zeman.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

21. Czech Translation of SQuAD 2.0 and 1.1

Creator:: Macková, Kateřina and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: SQuAD and reading comprehension
Language:: Czech
Description:: The Czech translation of SQuAD 2.0 and SQuAD 1.1 datasets contains automatically translated texts, questions and answers from the training set and the development set of the respective datasets. The test set is missing, because it is not publicly available. The data is released under the CC BY-NC-SA 4.0 license. If you use the dataset, please cite the following paper (the exact format was not available during the submission of the dataset): Kateřina Macková and Straka Milan: Reading Comprehension in Czech via Machine Translation and Cross-lingual Transfer, presented at TSD 2020, Brno, Czech Republic, September 8-11 2020.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

22. Czech Web Corpus 2017 (csTenTen17)

Creator:: Suchomel, Vít
Publisher:: Masaryk University, NLP Centre and Lexical Computing CZ s.r.o.
Type:: text and corpus
Subject:: Web corpus
Language:: Czech
Description:: The Czech Web Corpus 2017 (csTenTen17) is a Czech corpus made up of texts collected from the Internet, mostly from the Czech national top level domain ".cz". The data was crawled by web crawler SpiderLing (https://corpus.tools/wiki/SpiderLing). The data was cleaned by removing boilerplate (using https://corpus.tools/wiki/Justext), removing near-duplicate paragraphs (by https://corpus.tools/wiki/Onion) and discarding paragraphs not in the target language. The corpus was POS annotated by morphological analyser Majka using this POS tagset: https://www.sketchengine.eu/tagset-reference-for-czech/. Text sources: General web, Wikipedia. Time span of crawling: May, October and November 2017, October and November 2016, October and November 2015. The Czech Wikipedia part was downloaded in November 2017. Data format: Plain text, vertical (one token per line), gzip compressed. There are the following structures in the vertical: Documents (<doc/>, usually corresponding to web pages), paragraphs (<p/>), sentences (<s/>) and word join markers (<g/>, a "glue" tag indicating that there was no space between the surrounding tokens in the original text). Document metadata: src (the source of the data), title (the title of the web page), url (the URL of the document), crawl_date (the date of downloading the document). Paragraph metadata: heading ("1" if the paragraph is a heading, usually <h1> to <h6> elements in the original HTML data). Block elements in the case of an HTML source or double blank lines in the case of other source formats were used as paragraph separators. An internal heuristic tool was used to mark sentence breaks. The tab-separated positional attributes are: word form, morphological annotation, lem-POS (the base form of the word, i.e. the lemma, with a part of speech suffix) and gender respecting lemma (nouns and adjectives only). Please cite the following paper when using the corpus for your research: Suchomel, Vít. csTenTen17, a Recent Czech Web Corpus. In Recent Advances in Slavonic Natural Language Processing, pp. 111–123. 2018. (https://nlp.fi.muni.cz/raslan/raslan18.pdf#page=119)
Rights:: NLP Centre Web Corpus License, https://lindat.mff.cuni.cz/repository/xmlui/page/license-NLPC-WeC, and ACA

23. Danish Fungi 2020

Creator:: Picek, Lukáš, Šulc, Milan, Matas, Jiří, Jeppesen, Thomas S., Heilmann-Clausen, Jacob, Læssøe, Thomas, and Frøslev, Tobias
Publisher:: IEEE/CVF
Type:: IMAGE and corpus
Subject:: Fungi, image processing, Classification, and Fine-grained
Description:: Danish Fungi 2020 (DF20) is a fine-grained dataset and benchmark. The dataset, constructed from observations submitted to the Danish Fungal Atlas, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata, and well-defined class hierarchy. DF20 has zero overlap with ImageNet, allowing unbiased comparison of models fine-tuned from publicly available ImageNet checkpoints. The dataset has 1,604 different classes, with 248,466 training images and 27,608 test images.
Rights:: GNU Library or "Lesser" General Public License 3.0 (LGPL-3.0), http://opensource.org/licenses/LGPL-3.0, and PUB

27. Digital humanities: Introduction. A 10-week course with practical sessions.

Creator:: Nevěřilová, Zuzana
Publisher:: Masaryk University, Brno
Type:: VIDEO and onlineCourse
Subject:: data-driven research, digital content processing, text processing, image processing, metadata, word embeddings, evaluation, and research infrastructures
Language:: English
Description:: The aim of the course is to introduce digital humanities and to describe various aspects of digital content processing. The course consists of 10 lessons with video material and a PowerPoint presentation with the same content. Every lesson contains a practical session – either a Jupyter Notebook to work in Python or a text file with a short description of the task. Most of the practical tasks consist of running the programme and analyse the results. Although the course does not focus on programming, the code can be reused easily in individual projects. Some experience in running Python code is desirable but not required.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

28. ELITR Minuting Corpus

Creator:: Nedoluzhko, Anna, Singh, Muskaan, Hledíková, Marie, Tirthankar, Ghosal, and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: summarization, minuting, and meeting minutes
Language:: English and Czech
Description:: ELITR Minuting Corpus consists of transcripts of meetings in Czech and English, their manually created summaries ("minutes") and manual alignments between the two. Czech meetings are in the computer science and public administration domains and English meetings are in the computer science domain. Each transcript has one or multiple corresponding minutes files. Alignments are only provided for a portion of the data. This corpus contains 59 Czech and 120 English meeting transcripts, consisting of 71097 and 87322 dialogue turns respectively. For Czech meetings, we provide 147 total minutes with 55 of them aligned. For English meetings, it is 256 total minutes with 111 of them aligned. Please find a more detailed description of the data in the included README and stats.tsv files. If you use this corpus, please cite: Nedoluzhko, A., Singh, M., Hledíková, M., Ghosal, T., and Bojar, O. (2022). ELITR Minuting Corpus: A novel dataset for automatic minuting from multi-party meetings in English and Czech. In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC-2022), Marseille, France, June. European Language Resources Association (ELRA). In print. @inproceedings{elitr-minuting-corpus:2022, author = {Anna Nedoluzhko and Muskaan Singh and Marie Hled{\'{\i}}kov{\'{a}} and Tirthankar Ghosal and Ond{\v{r}}ej Bojar}, title = {{ELITR} {M}inuting {C}orpus: {A} Novel Dataset for Automatic Minuting from Multi-Party Meetings in {E}nglish and {C}zech}, booktitle = {Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC-2022)}, year = 2022, month = {June}, address = {Marseille, France}, publisher = {European Language Resources Association (ELRA)}, note = {In print.} }
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

29. EMMT (Eyetracked Multi-Modal Translation)

Creator:: Bhattacharya, Sunit, Kloudová, Věra, Zouhar, Vilém, and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: audio and corpus
Subject:: sight translation and multi-modal
Language:: English and Czech
Description:: Eyetracked Multi-Modal Translation (EMMT) is a simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenarios. It contains monocular eye movement recordings, audio data and 4-electrode wearable electroencephalogram (EEG) data of 43 participants while engaged in sight translation supported by an image. The details about the experiment and the dataset can be found in the README file.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

30. EngVallex - English Valency Lexicon 2.0

Creator:: Cinková, Silvie, Fučíková, Eva, Šindlerová, Jana, and Hajič, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, computationalLexicon, and lexicalConceptualResource
Subject:: Annotations, corpus, linguistic data, lexicon, lexical semantics, Monolingual, semantics, verbal valency, and valency
Language:: English
Description:: EngVallex 2.0 as a slightly updated version of EngVallex. It is the English counterpart of the PDT-Vallex valency lexicon, using the same view of valency, valency frames and the description of a surface form of verbal arguments. EngVallex contains links also to PropBank (English predicate-argument lexicon). The EngVallex lexicon is fully linked to the English side of the PCEDT parallel treebank(s), which is in fact the PTB re-annotated using the Prague Dependency Treebank style of annotation. The EngVallex is available in an XML format in our repository, and also in a searchable form with examples from the PCEDT. EngVallex 2.0 is the same dataset as the EngVallex lexicon packaged with the PCEDT 3.0 corpus, but published separately under a more permissive licence, avoiding the need for LDC licence which is tied to PCEDT 3.0 as a whole.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

31. EvaLatin 2020 models for UDPipe 2 (2020-08-31)

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: POS tagger, lemmatization, and tagger
Language:: Latin
Description:: POS Tagger and Lemmatizer models for EvaLatin2020 data (https://github.com/CIRCSE/LT4HALA). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#evalatin20_models . To use these models, you need UDPipe version at least 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

32. FAUST cs-en 0.5

Creator:: Hajič, Jan, Mareček, David, Fučíková, Eva, Cinková, Silvie, Štěpánek, Jan, Mikulová, Marie, and Popel, Martin
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: noisy texts, parallel corpus, and machine translation
Language:: English and Czech
Description:: This machine translation test set contains 2223 Czech sentences collected within the FAUST project (https://ufal.mff.cuni.cz/grants/faust, http://hdl.handle.net/11234/1-3308). Each original (noisy) sentence was normalized (clean1 and clean2) and translated to English independently by two translators.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

33. GECCC Grammar Error Correction Corpus for Czech

Creator:: Náplava, Jakub, Straka, Milan, Straková, Jana, and Rosen, Alexandr
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: gec, grammatical error correction, and dataset
Language:: Czech
Description:: Grammar Error Correction Corpus for Czech (GECCC) consists of 83 058 sentences and covers four diverse domains, including essays written by native students, informal website texts, essays written by Romani ethnic minority children and teenagers and essays written by nonnative speakers. All domains are professionally annotated for GEC errors in a unified manner, and errors were automatically categorized with a Czech-specific version of ERRANT released at https://github.com/ufal/errant_czech The dataset was introduced in the paper Czech Grammar Error Correction with a Large and Diverse Corpus that was accepted to TACL. Until published in TACL, see the arXiv version: https://arxiv.org/pdf/2201.05590.pdf
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), PUB, and http://creativecommons.org/licenses/by-sa/4.0/

34. GECCC Grammar Error Correction Corpus for Czech (2022-09-28)

Creator:: Náplava, Jakub, Straka, Milan, Straková, Jana, and Rosen, Alexandr
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: gec, grammatical error correction, and dataset
Language:: Czech
Description:: Grammar Error Correction Corpus for Czech (GECCC) consists of 83 058 sentences and covers four diverse domains, including essays written by native students, informal website texts, essays written by Romani ethnic minority children and teenagers and essays written by nonnative speakers. All domains are professionally annotated for GEC errors in a unified manner, and errors were automatically categorized with a Czech-specific version of ERRANT released at https://github.com/ufal/errant_czech The dataset was introduced in the paper Czech Grammar Error Correction with a Large and Diverse Corpus that was accepted to TACL. Until published in TACL, see the arXiv version: https://arxiv.org/pdf/2201.05590.pdf This version fixes double annotation errors in train and dev M2 files, and also contains more metadata information.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), PUB, and http://creativecommons.org/licenses/by-sa/4.0/

35. Hausa Visual Genome 1.0

Creator:: Abdulmumin, Idris, Das, Satya Ranja, Dawud, Musa Abdullahi, Parida, Shantipriya, Muhammad, Shamsuddeen Hassan, Ahmad, Ibrahim Sa'id, Panda, Subhadarshi, Bojar, Ondřej, Galadanci, Bashir Shehu, and Bello, Bello Shehu
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: image and corpus
Subject:: multi-modal, machine translation, image captioning, image annotation, and neural machine translation
Language:: Hausa and English
Description:: Data ------- Hausa Visual Genome 1.0, a multimodal dataset consisting of text and images suitable for English-to-Hausa multimodal machine translation tasks and multimodal research. We follow the same selection of short English segments (captions) and the associated images from Visual Genome as the dataset Hindi Visual Genome 1.1 has. We automatically translated the English captions to Hausa and manually post-edited, taking the associated images into account. The training set contains 29K segments. Further 1K and 1.6K segments are provided in development and test sets, respectively, which follow the same (random) sampling from the original Hindi Visual Genome. Additionally, a challenge test set of 1400 segments is available for the multi-modal task. This challenge test set was created in Hindi Visual Genome by searching for (particularly) ambiguous English words based on the embedding similarity and manually selecting those where the image helps to resolve the ambiguity. Dataset Formats ----------------------- The multimodal dataset contains both text and images. The text parts of the dataset (train and test sets) are in simple tab-delimited plain text files. All the text files have seven columns as follows: Column1 - image_id Column2 - X Column3 - Y Column4 - Width Column5 - Height Column6 - English Text Column7 - Hausa Text The image part contains the full images with the corresponding image_id as the file name. The X, Y, Width, and Height columns indicate the rectangular region in the image described by the caption. Data Statistics -------------------- The statistics of the current release are given below. Parallel Corpus Statistics ----------------------------------- Dataset Segments English Words Hausa Words ---------- -------- ------------- ----------- Train 28930 143106 140981 Dev 998 4922 4857 Test 1595 7853 7736 Challenge Test 1400 8186 8752 ---------- -------- ------------- ----------- Total 32923 164067 162326 The word counts are approximate, prior to tokenization. Citation ----------- If you use this corpus, please cite the following paper: @InProceedings{abdulmumin-EtAl:2022:LREC, author = {Abdulmumin, Idris and Dash, Satya Ranjan and Dawud, Musa Abdullahi and Parida, Shantipriya and Muhammad, Shamsuddeen and Ahmad, Ibrahim Sa'id and Panda, Subhadarshi and Bojar, Ond{\v{r}}ej and Galadanci, Bashir Shehu and Bello, Bello Shehu}, title = "{Hausa Visual Genome: A Dataset for Multi-Modal English to Hausa Machine Translation}", booktitle = {Proceedings of the Language Resources and Evaluation Conference}, month = {June}, year = {2022}, address = {Marseille, France}, publisher = {European Language Resources Association}, pages = {6471--6479}, url = {https://aclanthology.org/2022.lrec-1.694} }
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

36. Image Annotation Tool

Creator:: Roček, Martin
Publisher:: Charles University, Faculty of Arts
Type:: service and toolService
Subject:: tei and javascript
Language:: English
Description:: Image annotation tool is a web application that allows users to mark zones of interest in an image. These zones are then converted to TEI P5 code snippet that can be used in your document to connect the image and the text. This tool was developed to help students and teachers at the Faculty of Arts, Charles University to mark and annotate images of manuscripts.
Rights:: GNU General Public Licence, version 3, http://opensource.org/licenses/GPL-3.0, and PUB

37. IWPT 2020 Shared Task Data and System Outputs

Creator:: Zeman, Daniel, Bouma, Gosse, and Seddah, Djamé
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, enhanced universal dependencies, shared task, and parsing
Language:: Arabic, Bulgarian, Czech, Dutch, English, Estonian, Finnish, French, Italian, Latvian, Lithuanian, Polish, Russian, Slovak, Swedish, Tamil, and Ukrainian
Description:: This package contains data used in the IWPT 2020 shared task. It contains training, development and test (evaluation) datasets. The data is based on a subset of Universal Dependencies release 2.5 (http://hdl.handle.net/11234/1-3105) but some treebanks contain additional enhanced annotations. Moreover, not all of these additions became part of Universal Dependencies release 2.6 (http://hdl.handle.net/11234/1-3226), which makes the shared task data unique and worth a separate release to enable later comparison with new parsing algorithms. The package also contains a number of Perl and Python scripts that have been used to process the data during preparation and during the shared task. Finally, the package includes the official primary submission of each team participating in the shared task.
Rights:: Licence Universal Dependencies v2.5, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.5, and PUB

38. IWPT 2021 Shared Task Data and System Outputs

Creator:: Zeman, Daniel, Bouma, Gosse, and Seddah, Djamé
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, enhanced universal dependencies, shared task, and parsing
Language:: Arabic, Bulgarian, Czech, Dutch, English, Estonian, Finnish, French, Italian, Latvian, Lithuanian, Polish, Russian, Slovak, Swedish, Tamil, and Ukrainian
Description:: This package contains data used in the IWPT 2021 shared task. It contains training, development and test (evaluation) datasets. The data is based on a subset of Universal Dependencies release 2.7 (http://hdl.handle.net/11234/1-3424) but some treebanks contain additional enhanced annotations. Moreover, not all of these additions became part of Universal Dependencies release 2.8 (http://hdl.handle.net/11234/1-3687), which makes the shared task data unique and worth a separate release to enable later comparison with new parsing algorithms. The package also contains a number of Perl and Python scripts that have been used to process the data during preparation and during the shared task. Finally, the package includes the official primary submission of each team participating in the shared task.
Rights:: Licence Universal Dependencies v2.7, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.7, and PUB

39. LongEval Click-Model Relevance Judgements (Qrels)

Creator:: Galuščáková, Petra, Devaud, Romain, Gonzalez-Saez, Gabriela, Mulhem, Philippe, Goeuriot, Lorraine, Piroi, Florina, and Popel, Martin
Publisher:: Université Grenoble Alpes
Type:: text and corpus
Subject:: information retrieval, automatic evaluation, and evaluation
Language:: French and English
Description:: The collection comprises the relevance judgments used in the 2023 LongEval Information Retrieval Lab (https://clef-longeval.github.io/), organized at CLEF. It consists of three sets of relevance judgments: 1) Relevance judgments for the heldout queries from the LongEval Train Collection (http://hdl.handle.net/11234/1-5010). 2) Relevance judgments for the short-term persistence (sub-task A) queries from the LongEval Test Collection (http://hdl.handle.net/11234/1-5139). 3) Relevance judgments for the long-term persistence (sub-task B) queries from the LongEval Test Collection (http://hdl.handle.net/11234/1-5139). These judgments were provided by the Qwant search engine (https://www.qwant.com) and were generated using a click model. The click model output was based on the clicks of Qwant's users, but it mitigates noise from raw user clicks caused by positional bias and also better safeguards users' privacy. Consequently, it can serve as a reliable soft relevance estimate for evaluating and training models. The collection includes a total of 1,420 judgments for the heldout queries, with 74 considered highly relevant and 326 deemed relevant. For the short-term sub-task queries, there are 12,217 judgments, including 762 highly relevant and 2,608 relevant ones. As for the long-term sub-task queries, there are 13,467 judgments, with 936 being highly relevant and 2,899 relevant.
Rights:: Qwant LongEval Attribution-NonCommercial-ShareAlike License, https://lindat.mff.cuni.cz/repository/xmlui/page/Qwant_LongEval_BY-NC-SA_License, and PUB

40. LongEval Test Collection

Creator:: Galuščáková, Petra, Devaud, Romain, Gonzalez-Saez, Gabriela, Mulhem, Philippe, Goeuriot, Lorraine, Piroi, Florina, and Popel, Martin
Publisher:: Université Grenoble Alpes, Qwant, Research Studios Austria, and Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: information retrieval, cross-language, cross-lingual information retrieval, parallel corpus, and search
Language:: French and English
Description:: The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection are the webpages which were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index. The collection serves as the official test collection for the 2023 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF. The collection contains test datasets for two organized sub-tasks: short-term persistence (sub-task A) and long-term persistence (sub-task B). The data for the short-term persistence sub-task was collected over July 2022 and this dataset contains 1,593,376 documents and 882 queries. The data for the long-term persistence sub-task was collected over September 2022 and this dataset consists of 1,081,334 documents and 923 queries. Apart from the original French versions of the webpages and queries, the collection also contains their translations into English.
Rights:: Qwant LongEval Attribution-NonCommercial-ShareAlike License, https://lindat.mff.cuni.cz/repository/xmlui/page/Qwant_LongEval_BY-NC-SA_License, and PUB

41. LongEval Train Collection

Creator:: Galuščáková, Petra, Devaud, Romain, Gonzalez-Saez, Gabriela, Mulhem, Philippe, Goeuriot, Lorraine, Piroi, Florina, and Popel, Martin
Publisher:: Université Grenoble Alpes, Qwant, Research Studios Austria, and Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: information retrieval, parallel corpus, search, and automatic evaluation
Language:: French and English
Description:: The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index. All the data were collected over June 2022. In total, the collection contains 672 train queries, with corresponding 9656 assessments coming from the Qwant click model, and 98 heldout queries. The set of documents consist of 1,570,734 downloaded, cleaned and filtered Web Pages. Apart from their original French versions, the collection also contains translations of the webpages and queries into English. The collection serves as the official training collection for the 2023 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF.
Rights:: Qwant LongEval Attribution-NonCommercial-ShareAlike License, PUB, and https://lindat.mff.cuni.cz/repository/xmlui/page/Qwant_LongEval_BY-NC-SA_License

42. Malach Center User Interface 1.0

Creator:: Kocián, Jiří and Obdržálek, Pavel
Publisher:: Malach Center for Visual History, Institute of Formal and Applied Linguistics, Charles University
Type:: tool and toolService
Subject:: digital humanities, database, search engine, Jews, Holocaust, History, Oral History, Visual History, and digital archive of cultural heritage
Description:: Source code of the first full and running version for the Malach Center User Interface, does not contain data or metadata fo the digital objects and resources.
Rights:: GNU General Public Licence, version 3, http://opensource.org/licenses/GPL-3.0, and PUB

43. MorfFlex CZ 2.0

Creator:: Hajič, Jan, Hlaváčová, Jaroslava, Mikulová, Marie, Straka, Milan, and Štěpánková, Barbora
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicalConceptualResource, and computationalLexicon
Subject:: morphological dictionary, morphology, and Czech
Language:: Czech
Description:: MorfFlex CZ 2.0 is the Czech morphological dictionary developed originally by Jan Hajič as a spelling checker and lemmatization dictionary. MorfFlex is a flat list of lemma-tag-wordform triples. For each wordform, full inflectional information is coded in a positional tag. Wordforms are organized into entries (paradigm instances or paradigms in short) according to their formal morphological behavior. The paradigm (set of wordforms) is identified by a unique lemma. Apart from traditional morphological categories, the description also contains some semantic, stylistic and derivational information. For more details see a comprehensive specification of the Czech morphological annotation http://ufal.mff.cuni.cz/techrep/tr64.pdf .
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

44. MorfFlex SK 170914

Creator:: Hajič, Jan and Hric, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, computationalLexicon, and lexicalConceptualResource
Subject:: Slovak and morphological dictionary
Language:: Slovak
Description:: Slovak morphological dictionary modeled after the Czech one. It consists of (word form, lemma, POS tag) triples, reusing the Czech morphological system for POS tags and lemma descriptions.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

45. NameTag 2

Creator:: Straková, Jana
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: named entity recognition and named entity recognizer
Description:: NameTag 2 is a named entity recognition tool. It recognizes named entities (e.g., names, locations, etc.) and can recognize both flat and embedded (nested) entities. NameTag 2 can be used either as a commandline tool or by requesting the NameTag webservice. NameTag webservice can be found at: https://lindat.mff.cuni.cz/services/nametag/ NameTag commandline tool can be downloaded from NameTag GitHub repository, branch nametag2: git clone https://github.com/ufal/nametag -b nametag2 Latest models and documentation can be found at: https://ufal.mff.cuni.cz/nametag/2 This software subject to the terms of the Mozilla Public License, v. 2.0 (http://mozilla.org/MPL/2.0/). The associated models are distributed under CC BY-NC-SA license. Please cite as: Jana Straková, Milan Straka, Jan Hajič (2019): Neural Architectures for Nested NER through Linearization. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 5326-5331, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-950737-48-2 (https://aclweb.org/anthology/papers/P/P19/P19-1527/)
Rights:: Mozilla Public License 2.0, http://opensource.org/licenses/MPL-2.0, and PUB

46. NameTag 2 Models (2020-08-31)

Creator:: Straková, Jana and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, mlmodel, and languageDescription
Subject:: named entity recognition
Language:: English, German, Dutch, Spanish, and Czech
Description:: NER models for NameTag 2, named entity recognition tool, for English, German, Dutch, Spanish and Czech. Model documentation including performance can be found here: https://ufal.mff.cuni.cz/nametag/2/models . These models are for NameTag 2, named entity recognition tool, which can be found here: https://ufal.mff.cuni.cz/nametag/2 .
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

47. NameTag 2 Models (2021-09-16)

Creator:: Straková, Jana and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, mlmodel, and languageDescription
Subject:: named entity recognition and NER
Language:: English, German, Dutch, Spanish, and Czech
Description:: NER models for NameTag 2, named entity recognition tool, for English, German, Dutch, Spanish and Czech. Model documentation including performance can be found here: https://ufal.mff.cuni.cz/nametag/2/models . These models are for NameTag 2, named entity recognition tool, which can be found here: https://ufal.mff.cuni.cz/nametag/2 .
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

48. NameTag service description

Creator:: Straková, Jana and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: service and toolService
Subject:: named entity recognition, NameTag, and WeblichtXML
Language:: Czech, German, English, Spanish, and Dutch
Description:: Metadata description of nametag (http://hdl.handle.net/11234/1-3633, https://lindat.mff.cuni.cz/services/nametag/) provided for weblicht.
Rights:: Not specified

49. NomVallex 2.0

Creator:: Kolářová, Veronika, Vernerová, Anna, and Klímová, Jana
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, machineReadableDictionary, and lexicalConceptualResource
Subject:: valency, Czech, lexicon, syntax, semantics, deverbal nouns, adjectival valency, deadjectival nouns, deverbal adjectives, primary adjectives, denominal adjectives, deadjectival adjectives, and noun valency
Language:: Czech
Description:: NomVallex 2.0 is a manually annotated valency lexicon of Czech nouns and adjectives, created in the theoretical framework of the Functional Generative Description and based on corpus data (the SYN series of corpora from the Czech National Corpus and the Araneum Bohemicum Maximum corpus). In total, NomVallex is comprised of 1027 lexical units contained in 570 lexemes, covering the following parts-of-speech and derivational categories: deverbal or deadjectival nouns, and deverbal, denominal, deadjectival or primary adjectives. Valency properties of a lexical unit are captured in a valency frame (modeled as a sequence of valency slots, each supplemented with a list of morphemic forms) and documented by corpus examples. In order to make it possible to study the relationship between valency behavior of base words and their derivatives, lexical units of nouns and adjectives in NomVallex are linked to their respective base lexical units (contained either in NomVallex itself or, in case of verbs, in the VALLEX lexicon), linking up to three parts-of-speech (i.e., noun – verb, adjective – verb, noun – adjective, and noun – adjective – verb). In order to facilitate comparison, this submission also contains abbreviated entries of the base verbs of these nouns and adjectives from the VALLEX lexicon and simplified entries of the covered nouns and adjectives from the PDT-Vallex lexicon.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

50. NomVallex I.

Creator:: Kolářová, Veronika, Vernerová, Anna, and Klímová, Jana
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, machineReadableDictionary, and lexicalConceptualResource
Subject:: valency, Czech, lexicon, syntax, semantics, nominal valency, and deverbal nouns
Language:: Czech
Description:: The NomVallex I. lexicon describes valency of Czech deverbal nouns belonging to three semantic classes, i.e. Communication (dotaz 'question'), Mental Action (plán 'plan') and Psych State (nenávist 'hatred'). It covers both stem-nominals and root-nominals (dotazování se 'asking' and dotaz 'question'). In total, the lexicon includes 505 lexical units in 248 lexemes. Valency properties are captured in the form of valency frames, specifying valency slots and their morphemic forms, and are exemplified by corpus examples. In order to facilitate comparison, this submission also contains abbreviated entries of the source verbs of these nouns from the Vallex lexicon and simplified entries of the covered nouns from the PDT-Vallex lexicon.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

51. On-line Dictionary of medieval latin in the Czech lands

Creator:: Ctibor, Jan and Nývlt, Pavel
Publisher:: Institute of Philosophy of the Czech Academy of Sciences
Type:: text, lexicon, and lexicalConceptualResource
Subject:: dictionary, latin, Medieval, digital humanities, lexicography, and Medieval Latin
Language:: Latin and Czech
Description:: The Dictionary of Medieval Latin in the Czech Lands registers and explains the vocabulary of Medieval Latin as used in the Czech lands since the beginnings of Latin writing in this area (from about 1000 CE) to 1500 CE, so far covering the letters A-M. For more information about the Dictionary, see the webpage of the Department of Medieval Lexicography of the Institute of Philosophy of Czech Academy of Sciences. The data uploaded present the on-line version of the dictionary (API and XML data), making it possible to put the application into operation at a localhost.
Rights:: Dictionary of Medieval Latin in the Czech Lands - digital version 2.2 License Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/license-lb, and ACA

52. Package of word embeddings of Czech from a large corpus

Creator:: Kyjánek, Lukáš and Bonami, Olivier
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, computationalLexicon, and lexicalConceptualResource
Subject:: word embeddings, word vectors, large corpus, word2vec, skipgram, and cbow
Language:: Czech
Description:: This package comprises eight models of Czech word embeddings trained by applying word2vec (Mikolov et al. 2013) to the currently most extensive corpus of Czech, namely SYN v9 (Křen et al. 2022). The minimum frequency threshold for including a word in the model was 10 occurrences in the corpus. The original lemmatisation and tagging included in the corpus were used for disambiguation. In the case of word embeddings of word forms, units comprise word forms and their tag from a positional tagset (cf. https://wiki.korpus.cz/doku.php/en:pojmy:tag) separated by '>', e.g., kočka>NNFS1-----A----. The published package provides models trained on both tokens and lemmas. In addition, the models combine training algorithms (CBOW and Skipgram) and dimensions of the resulting vectors (100 or 500), while the training window and negative sampling remained the same during the training. The package also includes files with frequencies of word forms (vocab-frequencies.forms) and lemmas (vocab-frequencies.lemmas).
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

53. ParCzech 3.0

Creator:: Kopp, Matyáš, Stankov, Vladislav, Bojar, Ondřej, Hladká, Barbora, and Straňák, Pavel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: audio and corpus
Subject:: Parliament of the Czech Republic, Chamber of Deputies, stenographic protocols, TEI encoding, and speech corpus
Language:: Czech
Description:: The ParCzech 3.0 corpus is the third version of ParCzech consisting of stenographic protocols that record the Chamber of Deputies’ meetings held in the 7th term (2013-2017) and the current 8th term (2017-Mar 2021). The protocols are provided in their original HTML format, Parla-CLARIN TEI format, and the format suitable for Automatic Speech Recognition. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2. The audio files are aligned with the texts in the annotated TEI files.
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

54. ParCzech PS7 1.0

Creator:: Hladká, Barbora, Kopp, Matyáš, and Straňák, Pavel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: Parliament of the Czech Republic, Chamber of Deputies, stenographic protocols, TEI encoding, and TEITOK
Language:: Czech
Description:: The ParCzech PS7 1.0 corpus is the very first member of the corpus family of data coming from the Parliament of the Czech Republic. ParCzech PS7 1.0 consists of stenographic protocols that record the Chamber of Deputies' meetings held in the 7th term between 2013-2017. The audio recordings are available as well. Transcripts are provided in the original HTML as harvested, and also converted into TEI-derived XML format for use in TEITOK corpus manager. The corpus is automatically enriched with the morphological and named-entity annotations using the procedures MorphoDita and NameTag.
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

55. ParCzech PS7 2.0

Creator:: Hladká, Barbora, Kopp, Matyáš, and Straňák, Pavel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: Parliament of the Czech Republic, Chamber of Deputies, stenographic protocols, TEI encoding, and TEITOK
Language:: Czech
Description:: The ParCzech PS7 2.0 corpus is the second version of ParCzech PS7 consisting of stenographic protocols that record the Chamber of Deputies' meetings held in the 7th term between 2013-2017. The protocols are provided in their original HTML format, TEI format and TEI-derived format to make them searchable in the TEITOK corpus manager. Their audio recordings are available as well. The corpus is automatically enriched with the morphological, syntactic, and named-entity annotations using the procedures UDPipe 2 and NameTag 2.
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

56. PDT-Vallex: Czech Valency lexicon linked to treebanks 4.0 (PDT-Vallex 4.0)

Creator:: Urešová, Zdeňka, Bémová, Alevtina, Fučíková, Eva, Hajič, Jan, Kolářová, Veronika, Mikulová, Marie, Pajas, Petr, Panevová, Jarmila, and Štěpánek, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, computationalLexicon, and lexicalConceptualResource
Subject:: verbal valency, valency, annotation, linguistic data, lexicon, lexical semantics, and PDT
Language:: Czech
Description:: The valency lexicon PDT-Vallex 4.0 has been built in close connection with the annotation of the Prague Dependency Treebank project (PDT) and its successors (mainly the Prague Czech-English Dependency Treebank project, PCEDT, the spoken language corpus (PDTSC) and corpus of user-generated texts in the project Faust). It contains over 14500 valency frames for almost 8500 verbs which occurred in the PDT, PCEDT, PDTSC and Faust corpora. In addition, there are nouns, adjectives and adverbs, linked from the PDT part only, increasing the total to over 17000 valency frames for 13000 words. All the corpora have been published in 2020 as the PDT-C 1.0 corpus with the PDT-Vallex 4.0 dictionary included; this is a copy of the dictionary published as a separate item for those not interested in the corpora themselves. It is available in electronically processable format (XML), and also in more human readable form including corpus examples (see the WEBSITE link below, and the links to its main publications elsewhere in this metadata). The main feature of the lexicon is its linking to the annotated corpora - each occurrence of each verb is linked to the appropriate valency frame with additional (generalized) information about its usage and surface morphosyntactic form alternatives. It replaces the previously published unversioned edition of PDT-Vallex from 2014.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

57. Prague Dependency Treebank - Consolidated 1.0 (PDT-C 1.0)

Creator:: Hajič, Jan, Bejček, Eduard, Bémová, Alevtina, Buráňová, Eva, Fučíková, Eva, Hajičová, Eva, Havelka, Jiří, Hlaváčová, Jaroslava, Homola, Petr, Ircing, Pavel, Kárník, Jiří, Kettnerová, Václava, Klyueva, Natalia, Kolářová, Veronika, Kučová, Lucie, Lopatková, Markéta, Mareček, David, Mikulová, Marie, Mírovský, Jiří, Nedoluzhko, Anna, Novák, Michal, Pajas, Petr, Panevová, Jarmila, Peterek, Nino, Poláková, Lucie, Popel, Martin, Popelka, Jan, Romportl, Jan, Rysová, Magdaléna, Semecký, Jiří, Sgall, Petr, Spoustová, Johanka, Straka, Milan, Straňák, Pavel, Synková, Pavlína, Ševčíková, Magda, Šindlerová, Jana, Štěpánek, Jan, Štěpánková, Barbora, Toman, Josef, Urešová, Zdeňka, Vidová Hladká, Barbora, Zeman, Daniel, Zikánová, Šárka, and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: treebank, dependency, tectogrammatics, topic-focus articulation, multiword expressions, coreference, bridging relations, discourse, morphology, syntax, tokenization, lemmatization, semantic relations, lexical semantics, lexicon, valency, speech reconstruction, clauses, speech recognition, and spoken corpus
Language:: Czech
Description:: A richly annotated and genre-diversified language resource, The Prague Dependency Treebank – Consolidated 1.0 (PDT-C 1.0, or PDT-C in short in the sequel) is a consolidated release of the existing PDT-corpora of Czech data, uniformly annotated using the standard PDT scheme. PDT-corpora included in PDT-C: Prague Dependency Treebank (the original PDT contents, written newspaper and journal texts from three genres); Czech part of Prague Czech-English Dependency Treebank (translated financial texts, from English), Prague Dependency Treebank of Spoken Czech (spoken data, including audio and transcripts and multiple speech reconstruction annotation); PDT-Faust (user-generated texts). The difference from the separately published original treebanks can be briefly described as follows: it is published in one package, to allow easier data handling for all the datasets; the data is enhanced with a manual linguistic annotation at the morphological layer and new version of morphological dictionary is enclosed; a common valency lexicon for all four original parts is enclosed. Documentation provides two browsing and editing desktop tools (TrEd and MEd) and the corpus is also available online for searching using PML-TQ.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

58. Processing of intraclausal garden-path structures in Czech

Creator:: Ceháková, Markéta and Chromý, Jan
Publisher:: Charles University, Faculty of Arts, Institute of Czech Language and Theory of Communication
Type:: text, other, and languageDescription
Subject:: psycholinguistic experiments, sentence processing, Czech, garden-path, reading comprehension, and syntax
Language:: Czech
Description:: Experimental materials, data and R scripts used in the paper "Garden-path sentences and the diversity of their (mis)representations" (Ceháková - Chromý, 2023).
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

59. Quality and Efficiency of Manual Annotation: Data from the Pre-annotation Bias Experiment (part of the PDT-C 2.0 project)

Creator:: Mikulová, Marie, Straka, Milan, Štěpánek, Jan, Štěpánková, Barbora, and Hajič, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: annotation, syntax, inter-annotator agreement, pre-annotation bias, annotation efficiency, and annotation quality
Language:: Czech
Description:: Input data, individual experimental annotations, and a complete and detailed overview of the measured results related to the experiment described in the referenced paper.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

60. Semantic annotation of noun/verb conversion in Czech

Creator:: Ševčíková, Magda, Kyjánek, Lukáš, Hledíková, Hana, and Staňková, Anna
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: other, text, and lexicalConceptualResource
Subject:: conversion, semantic, noun, verb, word formation, and Czech
Language:: Czech
Description:: The item contains a list of 2,058 noun/verb conversion pairs along with related formations (word-formation paradigms) provided with linguistic features, including semantic categories that characterize semantic relations between the noun and the verb in each conversion pair. Semantic categories were assigned manually by two human annotators based on a set of sentences containing the noun and the verb from individual conversion pairs. In addition to the list of paradigms, the item contains a set of 739 files (a separate file for each conversion pair) annotated by the annotators in parallel and a set of 2,058 files containing the final annotation, which is included in the list of paradigms.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), PUB, and http://creativecommons.org/licenses/by-nc-sa/4.0/

61. Slovak MorphoDiTa Models 170914

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, mlmodel, and languageDescription
Subject:: MorphoDiTa, Slovak, morphological analysis, morphological generation, and PoS tagging
Language:: Slovak
Description:: Slovak models for MorphoDiTa, providing morphological analysis, morphological generation and part-of-speech tagging. The morphological dictionary is created from MorfFlex SK 170914 and the PoS tagger is trained on automatically translated Prague Dependency Treebank 3.0 (PDT).
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

62. SnakeCLEF 2021

Creator:: Picek, Lukáš, Bolon, Isabelle, Durso, Andrew M., and Castañeda, Rafael Ruiz de
Publisher:: CEUR Workshop Proceedings (CEUR-WS.org)
Type:: IMAGE and corpus
Subject:: LifeCLEF, SnakeCLEF, global health, epidemiology, snake bite, snake, reptile, benchmark, biodiversity, machine learning, computer vision, and Classification
Language:: No linguistic content
Description:: The dataset with 409,679 images belonging to 772 snake species from 188 countries and all continents (386,006 images with labels targeted for development and 23,673 images without labels for testing). In addition, we provide a simple train/val (90% / 10%) split to validate preliminary results while ensuring the same species distributions. Furthermore, we prepared a compact subset (70,208 images) for fast prototyping. The test set data consists of 23,673 images submitted to the iNaturalist platform within the "first four months of 2021. All data were gathered from online biodiversity platforms (i.e., iNaturalist, HerpMapper) and further extended by data scraped from Flickr. The provided dataset has a heavy long-tailed class distribution, where the most frequent species (Thamnophis sirtalis) is represented by 22,163 images and the least frequent by just 10 (Achalinus formosanus).
Rights:: BSD 3-Clause "New" or "Revised" license, http://opensource.org/licenses/BSD-3-Clause, and PUB

63. SQAD 3.2

Creator:: Medveď, Marek
Publisher:: Masaryk University, NLP Centre
Type:: text and corpus
Subject:: QA, Question Answering, SQAD, and Czech QA
Language:: Czech
Description:: Simple question answering database version 3.2 (SQAD v3.2) created from Czech Wikipedia. The new version consists of more than 16000 records. Each record of SQAD consists of multiple files - question, answer extraction, answer selection, URL, question metadata, and in some cases, answer context.
Rights:: Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0), http://creativecommons.org/licenses/by-sa/3.0/, and PUB

64. SynSemClass 1.0

Creator:: Urešová, Zdeňka, Fučíková, Eva, Hajičová, Eva, and Hajič, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, predicate argument structure, semantic roles, bilingual corpus annotation, translational equivalence, comparative syntax, and comparative semantics
Language:: English and Czech
Description:: The SynSemClass synonym verb lexicon is a result of a project investigating semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English language resources, i.e., relating verb meanings with respect to contextually-based verb synonymy. The lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (http://verbs.colorado.edu/verbnet/index.html), PropBank (http://verbs.colorado.edu/%7Empalmer/projects/ace.html), Ontonotes (http://verbs.colorado.edu/html_groupings/), and English Wordnet (https://wordnet.princeton.edu/). Part of the dataset are files reflecting interannotator agreement.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

65. SynSemClass 3.5

Creator:: Urešová, Zdeňka, Fučíková, Eva, Hajičová, Eva, Hajič, Jan, Zaczynska, Karolina, and Rehm, Georg
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, predicate argument structure, semantic roles, bilingual corpus annotation, translational equivalence, comparative syntax, and comparative semantics
Language:: Czech, English, and German
Description:: The SynSemClass 3.5 synonym verb lexicon investigates semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English and German-English language resources, i.e., relates verb meanings with respect to contextually-based verb synonymy. The Czech lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), Vallex (http://hdl.handle.net/11234/1-3524), and CzEngVallex (http://hdl.handle.net/11234/1-1512). The English lexicon entries are linked to EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html), PropBank (http://propbank.github.io/), Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and English Wordnet (https://wordnet.princeton.edu/). The German lexicon entries are linked to Woxikon (https://synonyme.woxikon.de), E-VALBU (https://grammis.ids-mannheim.de/verbvalenz), and GUP (http://alanakbik.github.io/multilingual.html; https://github.com/UniversalDependencies/UD_German-GSD).
Rights:: Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), http://creativecommons.org/licenses/by-nc-nd/4.0/, and PUB

66. SynSemClass 4.0

Creator:: Urešová, Zdeňka, Bourgonje, Peter, Fučíková, Eva, Hajič, Jan, Hajičová, Eva, Rehm, Georg, Rysová, Kateřina, and Zaczynska, Karolina
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, predicate argument structure, semantic roles, bilingual corpus annotation, translational equivalence, comparative syntax, and comparative semantics
Language:: Czech, English, and German
Description:: The SynSemClass synonym verb lexicon version 4.0 investigates, with respect to contextually-based verb synonymy, semantic ‘equivalence’ of Czech, English, and German verb senses and their valency behavior in parallel Czech-English and German-English language resources. SynSemClass 4.0 is a multilingual event-type ontology based on classes of synonymous verb senses, complemented with semantic roles and links to existing semantic lexicons. The version 4.0 is not only enriched by an additional number of classes but in the context of content hierarchy, some classes have been merged. Compared to the older versions of the lexicon, the novelty is the definitions of classes and the definitions of roles. Czech lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), Vallex (http://hdl.handle.net/11234/1-3524), and CzEngVallex (http://hdl.handle.net/11234/1-1512). The English lexicon entries are linked to EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html), PropBank (http://propbank.github.io/), Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and English Wordnet (https://wordnet.princeton.edu/). The German lexicon entries are linked to Woxikon (https://synonyme.woxikon.de), E-VALBU (https://grammis.ids-mannheim.de/verbvalenz), and GUP (http://alanakbik.github.io/multilingual.html; https://github.com/UniversalDependencies/UD_German-GSD).
Rights:: Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), http://creativecommons.org/licenses/by-nc-nd/4.0/, and PUB

67. SynSemClass 5.0

Creator:: Urešová, Zdeňka, Alcaina, Cristina Fernández, Bourgonje, Peter, Fučíková, Eva, Hajič, Jan, Hajičová, Eva, Rehm, Georg, Rysová, Kateřina, and Zaczynska, Karolina
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, predicate argument structure, semantic roles, bilingual corpus annotation, translational equivalence, comparative syntax, comparative semantics, and meaning representation
Language:: Czech, English, German, and Spanish
Description:: The SynSemClass synonym verb lexicon version 5.0 is a multilingual resource that enriches previous editions of this event-type ontology with a new language, Spanish. The existing languages, English, Czech and German, are further substantially extended by a larger number of classes. SSC 5.0 data also contain lists (in a separate removed_cms.zip file) with originally (pre-)proposed but later rejected class members. All languages are organized into classes and have links to other lexical sources. In addition to the existing links, links to Spanish sources have been added. The Spanish entries are linked to ADESSE (http://adesse.uvigo.es/), Spanish SenSem (http://grial.edu.es/sensem/lexico?idioma=en), Spanish WordNet (https://adimen.si.ehu.es/cgi-bin/wei/public/wei.consult.perl), AnCora (https://clic.ub.edu/corpus/en/ancoraverb_es), and Spanish FrameNet (http://sfn.spanishfn.org/SFNreports.php). The English entries are linked to EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/) VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html), PropBank (http://propbank.github.io/), Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and English Wordnet (https://wordnet.princeton.edu/). Czech entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), Vallex (http://hdl.handle.net/11234/1-3524), and CzEngVallex (http://hdl.handle.net/11234/1-1512). The German entries are linked to Woxikon (https://synonyme.woxikon.de), E-VALBU (https://grammis.ids-mannheim.de/verbvalenz), and GUP (http://alanakbik.github.io/multilingual.html and https://github.com/UniversalDependencies/UD_German-GSD).
Rights:: Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), http://creativecommons.org/licenses/by-nc-nd/4.0/, and PUB

68. SynSemClass2.0

Creator:: Urešová, Zdeňka, Fučíková, Eva, Hajičová, Eva, and Hajič, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, predicate argument structure, semantic roles, bilingual corpus annotation, translational equivalence, comparative syntax, and comparative semantics
Language:: English and Czech
Description:: The SynSemClass synonym verb lexicon is a result of a project investigating semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English language resources, i.e., relating verb meanings with respect to contextually-based verb synonymy. The lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html), PropBank (http://propbank.github.io/), Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and English Wordnet (https://wordnet.princeton.edu/).
Rights:: Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), http://creativecommons.org/licenses/by-nc-nd/4.0/, and PUB

69. SynSemClass3.0

Creator:: Urešová, Zdeňka, Fučíková, Eva, Hajičová, Eva, and Hajič, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, predicate argument structure, semantic roles, bilingual corpus annotation, translational equivalence, comparative syntax, and comparative semantics
Language:: Czech and English
Description:: The SynSemClass synonym verb lexicon is a result of a project investigating semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English language resources, i.e., relating verb meanings with respect to contextually-based verb synonymy. The lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html), PropBank (http://propbank.github.io/), Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and English Wordnet (https://wordnet.princeton.edu/).
Rights:: Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), http://creativecommons.org/licenses/by-nc-nd/4.0/, and PUB

70. Synthetic part of CzEng 2.0

Creator:: Popel, Martin
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: parallel corpus
Language:: Czech and English
Description:: CzEng is a sentence-parallel Czech-English corpus compiled at the Institute of Formal and Applied Linguistics (ÚFAL). While the full CzEng 2.0 is freely available for non-commercial research purposes from the project website (https://ufal.mff.cuni.cz/czeng), this release contains only the original monolingual parts of news text (csmono 53M and enmono 79M sentences) with automatic (synthetic) translations by CUBBITT. See the attached README for additional details such as the file format.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB

71. UDPipe 2

Creator:: Straka, Milan and Straková, Jana
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: POS tagger, tagger, lemmatization, parser, dependency parser, and CoNLL-U
Description:: UDPipe 2 is a POS tagger, lemmatizer and dependency parser. Compared to UDPipe 1: - UDPipe 2 is Python-only and tested only in Linux, - UDPipe 2 is meant as a research tool, not as a user-friendly UDPipe 1 replacement, - UDPipe 2 achieves much better performance, but requires a GPU for reasonable performance, - UDPipe 2 does not perform tokenization by itself – it uses UDPipe 1 for that. UDPipe 2 is available in the udpipe-2 branch of the UDPipe repository at https://github.com/ufal/udpipe/tree/udpipe-2. It is a free software under Mozilla Public License 2.0 (http://www.mozilla.org/MPL/2.0/) and the models are free for non-commercial use and distributed under CC BY-NC-SA (http://creativecommons.org/licenses/by-nc-sa/4.0/) license, although for some models the original data used to create the model may impose additional licensing conditions. UDPipe 2 is also available as a REST service running at https://lindat.mff.cuni.cz/services/udpipe. If you like, you can use the https://github.com/ufal/udpipe/blob/udpipe-2/udpipe2_client.py script to interact with it.
Rights:: Not specified

72. Universal Dependencies 2.10

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Algom, Avner, Andersen, Erik, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranes, Glyd, Aranzabe, Maria Jesus, Arıcan, Bilge Nas, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Aslan, Deniz Baran, Asmazoğlu, Cengiz, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Barkarson, Starkaður, Basile, Rodolfo, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Bengoetxea, Kepa, Ben Moshe, Yifat, Berk, Gözde, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Braggaar, Anouck, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cassidy, Lauren, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cesur, Neslihan, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chauhan, Shweta, Chi, Ethan, Chika, Taishi, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Chung, Juyeon, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Corbetta, Daniela, Courtin, Marine, Cristescu, Mihaela, Daniel, Philemon, Davidson, Elizabeth, Dehouck, Mathieu, de Laurentiis, Martina, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Di Nuovo, Elisa, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Eckhoff, Hanne, Eiche, Sandra, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Favero, Federica, Ferdaousi, Jannatul, Fernanda, Marília, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Gamba, Federica, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerardi, Fabrício Ferraz, Gerdes, Kim, Ginter, Filip, Godoy, Gustavo, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Harada, Takahiro, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Ito, Kaoru, Jannat, Siratun, Jelínek, Tomáš, Jha, Apoorva, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, K, Sarveswaran, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Kara, Neslihan, Karahóǧa, Ritván, Katz, Boris, Kayadelen, Tolga, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Klyachko, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Köse, Mehmet, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kübler, Sandra, Kuyrukçu, Oğuzhan, Kuzgun, Aslı, Kwak, Sookyoung, Laippala, Veronika, Lam, Lucia, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yuan, Lim, KyungTae, Lima Padovani, Bruna, Lindén, Krister, Ljubešić, Nikola, Loginova, Olga, Lusito, Stefano, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Mahamdi, Menel, Maillard, Jean, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Marşan, Büşra, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Markantonatou, Stella, Martínez Alonso, Héctor, Martín Rodríguez, Lorena, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, Mazzei, Alessandro, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Merzhevich, Tatiana, Miekka, Niko, Mischenkova, Karina, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Molnár, Judit, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Moretti, Giovanni, Mori, Keiko Sophie, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nevaci, Manuela, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Ordan, Noam, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özçelik, Merve, Özgür, Arzucan, Öztürk Başaran, Balkız, Paccosi, Teresa, Palmero Aprosio, Alessio, Park, Hyunji Hayley, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Pedonese, Giulia, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Peverelli, Andrea, Phelan, Jason, Piitulainen, Jussi, Pirinen, Tommi A, Pitler, Emily, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Rahoman, Mizanur, Rama, Taraka, Ramasamy, Loganathan, Ramisch, Carlos, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Regnault, Mathilde, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rizqiyah, Putri, Rocha, Luisa, Rögnvaldsson, Eiríkur, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rozonoyer, Ben, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sagot, Benoît, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Sanıyar, Ezgi, Särg, Dage, Saulīte, Baiba, Sawanakunanon, Yanin, Saxena, Shefali, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Schwartz, Lane, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shahzadi, Syeda, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shishkina, Yana, Shohibussirri, Muh, Sichinava, Dmitry, Siewert, Janine, Sigurðsson, Einar Freyr, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Simov, Kiril, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Sourov, Shafi, Spadine, Carolyn, Sprugnoli, Rachele, Stamou, Vivian, Steingrímsson, Steinþór, Stella, Antonio, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Swanson, Daniel, Szántó, Zsolt, Taguchi, Chihiro, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tanaya, Dipta, Tavoni, Mirko, Tella, Samson, Tellier, Isabelle, Testori, Marinella, Thomas, Guillaume, Tonelli, Sara, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vagnoni, Elena, Vajjala, Sowmya, van der Goot, Rob, Vanhove, Martine, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Vedenina, Uliana, Villemonte de la Clergerie, Eric, Vincze, Veronika, Vlasova, Natalia, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Wigderson, Shira, Wijono, Sri Hartati, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yenice, Arife Betül, Yıldız, Olcay Taner, Yu, Zhuoran, Yuliawati, Arlisa, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhou, He, Zhu, Hanzhi, Zhuravleva, Anna, and Ziane, Rayan
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, Tupinambá, Beja, Western Frisian, Guajajára, Urubú-Kaapor, Kangri, K'iche', Low German, Makuráp, Central Siberian Yupik, Western Armenian, Bengali, Javanese, Karo (Brazil), Ligurian, Neapolitan, Tatar, Xibe, Yakut, Ancient Hebrew, Cebuano, Guarani, Hittite, Madi, Emerillon, and Umbrian
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Rights:: Licence Universal Dependencies v2.10, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.10, and PUB

73. Universal Dependencies 2.10 models for UDPipe 2 (2022-07-11)

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: tokenizer, POS tagger, lemmatization, tagger, parser, and dependency parser
Language:: Afrikaans, Arabic, Belarusian, Bulgarian, Catalan, Czech, Church Slavic, Coptic, Welsh, Danish, German, Modern Greek (1453-), English, Estonian, Basque, Faroese, Persian, Finnish, French, Old French (842-ca. 1400), Scottish Gaelic, Irish, Galician, Gothic, Ancient Greek (to 1453), Ancient Hebrew, Hebrew, Hindi, Croatian, Hungarian, Armenian, Western Armenian, Indonesian, Icelandic, Italian, Japanese, Korean, Latin, Latvian, Lithuanian, Literary Chinese, Marathi, Maltese, Dutch, Norwegian Nynorsk, Norwegian Bokmål, Old Russian, Nigerian Pidgin, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Northern Sami, Spanish, Serbian, Swedish, Tamil, Telugu, Turkish, Uighur, Ukrainian, Urdu, Vietnamese, Gambian Wolof, Wolof, and Chinese
Description:: Tokenizer, POS Tagger, Lemmatizer and Parser models for 123 treebanks of 69 languages of Universal Depenencies 2.10 Treebanks, created solely using UD 2.10 data (https://hdl.handle.net/11234/1-4758). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_210_models . To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

74. Universal Dependencies 2.11

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Akkurt, Salih Furkan, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Algom, Avner, Alzetta, Chiara, Andersen, Erik, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranes, Glyd, Aranzabe, Maria Jesus, Arıcan, Bilge Nas, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Ásgeirsdóttir, Katla, Aslan, Deniz Baran, Asmazoğlu, Cengiz, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Barkarson, Starkaður, Basile, Rodolfo, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Belieni, Juan, Bengoetxea, Kepa, Ben Moshe, Yifat, Berk, Gözde, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Braggaar, Anouck, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cassidy, Lauren, Castro, Maria Clara, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cesur, Neslihan, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chamila, Liyanage, Chauhan, Shweta, Chi, Ethan, Chika, Taishi, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Chung, Juyeon, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Corbetta, Daniela, Courtin, Marine, Cristescu, Mihaela, Daniel, Philemon, Davidson, Elizabeth, de Alencar, Leonel Figueiredo, Dehouck, Mathieu, de Laurentiis, Martina, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Di Nuovo, Elisa, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Ebert, Christian, Eckhoff, Hanne, Eiche, Sandra, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Favero, Federica, Ferdaousi, Jannatul, Fernanda, Marília, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Gamba, Federica, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerardi, Fabrício Ferraz, Gerdes, Kim, Ginter, Filip, Godoy, Gustavo, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Harada, Takahiro, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Huerta Mendez, Marivel, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Islamaj, Artan, Ito, Kaoru, Jannat, Siratun, Jelínek, Tomáš, Jha, Apoorva, Jiang, Katharine, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Kara, Neslihan, Karahóǧa, Ritván, Katz, Boris, Kayadelen, Tolga, Kengatharaiyer, Sarveswaran, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Klyachko, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Köse, Mehmet, Koshevoy, Alexey, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kübler, Sandra, Kuqi, Adrian, Kuyrukçu, Oğuzhan, Kuzgun, Aslı, Kwak, Sookyoung, Laippala, Veronika, Lam, Lucia, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yixuan, Li, Yuan, Lim, KyungTae, Lima Padovani, Bruna, Lindén, Krister, Ljubešić, Nikola, Loginova, Olga, Lusito, Stefano, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Mahamdi, Menel, Maillard, Jean, Makarchuk, Ilya, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Marşan, Büşra, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Markantonatou, Stella, Martínez Alonso, Héctor, Martín Rodríguez, Lorena, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, Mazzei, Alessandro, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Merzhevich, Tatiana, Miekka, Niko, Mischenkova, Karina, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Molnár, Judit, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Moretti, Giovanni, Mori, Keiko Sophie, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nevaci, Manuela, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Óladóttir, Hulda, Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Ordan, Noam, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özçelik, Merve, Özgür, Arzucan, Öztürk Başaran, Balkız, Paccosi, Teresa, Palmero Aprosio, Alessio, Panova, Anastasia, Park, Hyunji Hayley, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Pedonese, Giulia, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Peverelli, Andrea, Phelan, Jason, Piitulainen, Jussi, Pintucci, Rodrigo, Pirinen, Tommi A, Pitler, Emily, Plamada, Magdalena, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Pugh, Robert, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Rahoman, Mizanur, Rama, Taraka, Ramasamy, Loganathan, Ramisch, Carlos, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Regnault, Mathilde, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rizqiyah, Putri, Rocha, Luisa, Rögnvaldsson, Eiríkur, Roksandic, Ivan, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rozonoyer, Ben, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sagot, Benoît, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Sanıyar, Ezgi, Särg, Dage, Sartor, Marta, Sasaki, Mitsuya, Saulīte, Baiba, Sawanakunanon, Yanin, Saxena, Shefali, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Schwartz, Lane, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shahzadi, Syeda, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shishkina, Yana, Shohibussirri, Muh, Shvedova, Maria, Siewert, Janine, Sigurðsson, Einar Freyr, Silva, João Ricardo, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Símonarson, Haukur Barri, Simov, Kiril, Sitchinava, Dmitri, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Sonnenhauser, Barbara, Sourov, Shafi, Spadine, Carolyn, Sprugnoli, Rachele, Stamou, Vivian, Steingrímsson, Steinþór, Stella, Antonio, Stephen, Abishek, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Swanson, Daniel, Szántó, Zsolt, Taguchi, Chihiro, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tanaya, Dipta, Tavoni, Mirko, Tella, Samson, Tellier, Isabelle, Testori, Marinella, Thomas, Guillaume, Tonelli, Sara, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Þórðarson, Sveinbjörn, Þorsteinsson, Vilhjálmur, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vagnoni, Elena, Vajjala, Sowmya, van der Goot, Rob, Vanhove, Martine, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Vedenina, Uliana, Venturi, Giulia, Villemonte de la Clergerie, Eric, Vincze, Veronika, Vlasova, Natalia, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Wigderson, Shira, Wijono, Sri Hartati, Wille, Vanessa Berwanger, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yenice, Arife Betül, Yıldız, Olcay Taner, Yu, Zhuoran, Yuliawati, Arlisa, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhou, He, Zhu, Hanzhi, Zhuravleva, Anna, and Ziane, Rayan
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, Tupinambá, Beja, Western Frisian, Guajajára, Urubú-Kaapor, Kangri, K'iche', Low German, Makuráp, Central Siberian Yupik, Western Armenian, Bengali, Javanese, Karo (Brazil), Ligurian, Neapolitan, Tatar, Xibe, Yakut, Ancient Hebrew, Cebuano, Guarani, Hittite, Madi, Emerillon, Umbrian, Abaza, Gheg Albanian, Malayalam, Nhengatu, Sinhala, Zacatlán-Ahuacatlán-Tepetzintla Nahuatl, Xavánte, and Saya
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Rights:: Licence Universal Dependencies v2.11, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.11, and PUB

75. Universal Dependencies 2.12

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Akkurt, Salih Furkan, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Algom, Avner, Alnajjar, Khalid, Alzetta, Chiara, Andersen, Erik, Antonsen, Lene, Aoyama, Tatsuya, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranes, Glyd, Aranzabe, Maria Jesus, Arıcan, Bilge Nas, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Ásgeirsdóttir, Katla, Aslan, Deniz Baran, Asmazoğlu, Cengiz, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Avelãs, Mariana, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Barkarson, Starkaður, Basile, Rodolfo, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Behzad, Shabnam, Bengoetxea, Kepa, Benli, İbrahim, Ben Moshe, Yifat, Berk, Gözde, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Braggaar, Anouck, Branco, António, Brokaitė, Kristina, Burchardt, Aljoscha, Campos, Marisa, Candito, Marie, Caron, Bernard, Caron, Gauthier, Carvalheiro, Catarina, Carvalho, Rita, Cassidy, Lauren, Castro, Maria Clara, Castro, Sérgio, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cesur, Neslihan, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chamila, Liyanage, Chauhan, Shweta, Chi, Ethan, Chika, Taishi, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Chung, Juyeon, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Corbetta, Daniela, Costa, Francisco, Courtin, Marine, Cristescu, Mihaela, Dale, Ingerid Løyning, Daniel, Philemon, Davidson, Elizabeth, de Alencar, Leonel Figueiredo, Dehouck, Mathieu, de Laurentiis, Martina, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Di Nuovo, Elisa, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Doyle, Adrian, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Ebert, Christian, Eckhoff, Hanne, Eguchi, Masaki, Eiche, Sandra, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Essaidi, Farah, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Favero, Federica, Ferdaousi, Jannatul, Fernanda, Marília, Fernandez Alcalde, Hector, Fethi, Amal, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Gamba, Federica, Garcia, Marcos, Gärdenfors, Moa, Gerardi, Fabrício Ferraz, Gerdes, Kim, Gessler, Luke, Ginter, Filip, Godoy, Gustavo, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Harada, Takahiro, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Huerta Mendez, Marivel, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Islamaj, Artan, Ito, Kaoru, Jannat, Siratun, Jelínek, Tomáš, Jha, Apoorva, Jiang, Katharine, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, Kaşıkara, Hüner, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Kara, Neslihan, Karahóǧa, Ritván, Kåsen, Andre, Kayadelen, Tolga, Kengatharaiyer, Sarveswaran, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Klyachko, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Köse, Mehmet, Koshevoy, Alexey, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kübler, Sandra, Kuqi, Adrian, Kuyrukçu, Oğuzhan, Kuzgun, Aslı, Kwak, Sookyoung, Kyle, Kris, Laippala, Veronika, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Levine, Lauren, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yixuan, Li, Yuan, Lim, KyungTae, Lima Padovani, Bruna, Lin, Yi-Ju Jessica, Lindén, Krister, Liu, Yang Janet, Ljubešić, Nikola, Loginova, Olga, Lusito, Stefano, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Mahamdi, Menel, Maillard, Jean, Makarchuk, Ilya, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Marşan, Büşra, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Markantonatou, Stella, Martínez Alonso, Héctor, Martín Rodríguez, Lorena, Martins, André, Martins, Cláudia, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, Mazzei, Alessandro, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Merzhevich, Tatiana, Miekka, Niko, Miller, Aaron, Mischenkova, Karina, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Molnár, Judit, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Moretti, Giovanni, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nevaci, Manuela, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Óladóttir, Hulda, Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Ordan, Noam, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özçelik, Merve, Özgür, Arzucan, Öztürk Başaran, Balkız, Paccosi, Teresa, Palmero Aprosio, Alessio, Panova, Anastasia, Park, Hyunji Hayley, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Pedonese, Giulia, Peljak-Łapińska, Angelika, Peng, Siyao, Peng, Siyao Logan, Pereira, Rita, Pereira, Sílvia, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Peverelli, Andrea, Phelan, Jason, Piitulainen, Jussi, Pinter, Yuval, Pinto, Clara, Pirinen, Tommi A, Pitler, Emily, Plamada, Magdalena, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Pugh, Robert, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Querido, Andreia, Rääbis, Andriela, Rademaker, Alexandre, Rahoman, Mizanur, Rama, Taraka, Ramasamy, Loganathan, Ramos, Joana, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Regnault, Mathilde, Rehm, Georg, Riabi, Arij, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rizqiyah, Putri, Rocha, Luisa, Rögnvaldsson, Eiríkur, Roksandic, Ivan, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rozonoyer, Ben, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Sanıyar, Ezgi, Särg, Dage, Sartor, Marta, Sasaki, Mitsuya, Saulīte, Baiba, Sawanakunanon, Yanin, Saxena, Shefali, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Schwartz, Lane, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shahzadi, Syeda, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shishkina, Yana, Shohibussirri, Muh, Shvedova, Maria, Siewert, Janine, Sigurðsson, Einar Freyr, Silva, João, Silveira, Aline, Silveira, Natalia, Silveira, Sara, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Símonarson, Haukur Barri, Simov, Kiril, Sitchinava, Dmitri, Sither, Ted, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Solberg, Per Erik, Sonnenhauser, Barbara, Sourov, Shafi, Sprugnoli, Rachele, Stamou, Vivian, Steingrímsson, Steinþór, Stella, Antonio, Stephen, Abishek, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Swanson, Daniel, Szántó, Zsolt, Taguchi, Chihiro, Taji, Dima, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tanaya, Dipta, Tavoni, Mirko, Tella, Samson, Tellier, Isabelle, Testori, Marinella, Thomas, Guillaume, Tonelli, Sara, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Þórðarson, Sveinbjörn, Þorsteinsson, Vilhjálmur, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vagnoni, Elena, Vajjala, Sowmya, Vak, Socrates, van der Goot, Rob, Vanhove, Martine, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Vedenina, Uliana, Venturi, Giulia, Vincze, Veronika, Vlasova, Natalia, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Wigderson, Shira, Wijono, Sri Hartati, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yenice, Arife Betül, Yıldız, Olcay Taner, Yu, Zhuoran, Yuliawati, Arlisa, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhou, He, Zhu, Hanzhi, Zhu, Yilun, Zhuravleva, Anna, and Ziane, Rayan
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, Tupinambá, Beja, Western Frisian, Guajajára, Urubú-Kaapor, Kangri, K'iche', Low German, Makuráp, Central Siberian Yupik, Western Armenian, Bengali, Javanese, Karo (Brazil), Ligurian, Neapolitan, Tatar, Xibe, Yakut, Ancient Hebrew, Cebuano, Guarani, Hittite, Madi, Emerillon, Umbrian, Abaza, Gheg Albanian, Malayalam, Nhengatu, Sinhala, Zacatlán-Ahuacatlán-Tepetzintla Nahuatl, Xavánte, Saya, Borôro, Kirghiz, Algerian Arabic, and Old Irish (to 900)
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Rights:: Licence Universal Dependencies v2.12, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.12, and PUB

76. Universal Dependencies 2.6

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Agić, Željko, Ahrenberg, Lars, Ajede, Chika Kennedy, Aleksandravičiūtė, Gabrielė, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aranzabe, Maria Jesus, Arutie, Gashaw, Asahara, Masayuki, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bengoetxea, Kepa, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cetin, Savas, Chalub, Fabricio, Chi, Ethan, Choi, Jinho, Cho, Yongseok, Chun, Jayeol, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Courtin, Marine, Davidson, Elizabeth, de Marneffe, Marie-Catherine, de Paiva, Valeria, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Eckhoff, Hanne, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Farkas, Richárd, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerdes, Kim, Ginter, Filip, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Hwang, Jena, Ikeda, Takumi, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Jelínek, Tomáš, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Katz, Boris, Kayadelen, Tolga, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Kwak, Sookyoung, Laippala, Veronika, Lambertino, Lorenzo, Lam, Lucia, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Lim, KyungTae, Li, Yuan, Ljubešić, Nikola, Loginova, Olga, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Martínez Alonso, Héctor, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Miekka, Niko, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Mori, Keiko Sophie, Morioka, Tomohiko, Mori, Shinsuke, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özgür, Arzucan, Öztürk Başaran, Balkız, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perrier, Guy, Petrova, Daria, Petrov, Slav, Phelan, Jason, Piitulainen, Jussi, Pirinen, Tommi A, Pitler, Emily, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Ramasamy, Loganathan, Rama, Taraka, Ramisch, Carlos, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rocha, Luisa, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rudina, Olga, Rueter, Jack, Sadde, Shoval, Sagot, Benoît, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Särg, Dage, Saulīte, Baiba, Sawanakunanon, Yanin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shohibussirri, Muh, Sichinava, Dmitry, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Simov, Kiril, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Spadine, Carolyn, Stella, Antonio, Straka, Milan, Strnadová, Jana, Suhr, Alane, Sulubacak, Umut, Suzuki, Shingo, Szántó, Zsolt, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tanaka, Takaaki, Tella, Samson, Tellier, Isabelle, Thomas, Guillaume, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vajjala, Sowmya, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Villemonte de la Clergerie, Eric, Vincze, Veronika, Wakasa, Aya, Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yu, Zhuoran, Žabokrtský, Zdeněk, Zeldes, Amir, Zhu, Hanzhi, and Zhuravleva, Anna
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, and Icelandic
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Rights:: Licence Universal Dependencies v2.6, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.6, and PUB

77. Universal Dependencies 2.6 models for UDPipe 2 (2020-08-31)

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: tokenizer, POS tagger, lemmatization, tagger, parser, and dependency parser
Language:: Afrikaans, Arabic, Armenian, Belarusian, Bulgarian, Catalan, Czech, Church Slavic, Coptic, Welsh, Danish, German, Modern Greek (1453-), English, Estonian, Basque, Persian, Finnish, French, Old French (842-ca. 1400), Scottish Gaelic, Irish, Galician, Gothic, Ancient Greek (to 1453), Hebrew, Hindi, Croatian, Hungarian, Indonesian, Italian, Japanese, Korean, Latin, Latvian, Lithuanian, Literary Chinese, Marathi, Maltese, Dutch, Norwegian Nynorsk, Norwegian Bokmål, Old Russian, Nigerian Pidgin, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Northern Sami, Spanish, Serbian, Swedish, Tamil, Telugu, Turkish, Uighur, Ukrainian, Urdu, Vietnamese, Gambian Wolof, Wolof, and Chinese
Description:: Tokenizer, POS Tagger, Lemmatizer and Parser models for 99 treebanks of 63 languages of Universal Depenencies 2.6 Treebanks, created solely using UD 2.6 data (https://hdl.handle.net/11234/1-3226). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_26_models . To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

78. Universal Dependencies 2.7

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranzabe, Maria Jesus, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Bengoetxea, Kepa, Berk, Gözde, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chi, Ethan, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Courtin, Marine, Davidson, Elizabeth, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Eckhoff, Hanne, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Fernanda, Marília, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerardi, Fabrício Ferraz, Gerdes, Kim, Ginter, Filip, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Huber, Eva, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Jelínek, Tomáš, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, K, Sarveswaran, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Katz, Boris, Kayadelen, Tolga, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kwak, Sookyoung, Laippala, Veronika, Lam, Lucia, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yuan, Lim, KyungTae, Lindén, Krister, Ljubešić, Nikola, Loginova, Olga, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Martínez Alonso, Héctor, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Miekka, Niko, Mischenkova, Karina, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Mori, Keiko Sophie, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özgür, Arzucan, Öztürk Başaran, Balkız, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Phelan, Jason, Piitulainen, Jussi, Pirinen, Tommi A, Pitler, Emily, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Rama, Taraka, Ramasamy, Loganathan, Ramisch, Carlos, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rocha, Luisa, Rögnvaldsson, Eiríkur, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sagot, Benoît, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Särg, Dage, Saulīte, Baiba, Sawanakunanon, Yanin, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shohibussirri, Muh, Sichinava, Dmitry, Sigurðsson, Einar Freyr, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Simov, Kiril, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Spadine, Carolyn, Steingrímsson, Steinþór, Stella, Antonio, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Szántó, Zsolt, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tella, Samson, Tellier, Isabelle, Thomas, Guillaume, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vajjala, Sowmya, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Villemonte de la Clergerie, Eric, Vincze, Veronika, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yu, Zhuoran, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhu, Hanzhi, and Zhuravleva, Anna
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, and Tupinambá
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Rights:: Licence Universal Dependencies v2.7, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.7, and PUB

79. Universal Dependencies 2.8

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranzabe, Maria Jesus, Arıcan, Bilge Nas, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Aslan, Deniz Baran, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Barkarson, Starkaður, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Bengoetxea, Kepa, Berk, Gözde, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Braggaar, Anouck, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cassidy, Lauren, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cesur, Neslihan, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chauhan, Shweta, Chi, Ethan, Chika, Taishi, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Courtin, Marine, Cristescu, Mihaela, Daniel, Philemon., Davidson, Elizabeth, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Di Nuovo, Elisa, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Eckhoff, Hanne, Eiche, Sandra, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Fernanda, Marília, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerardi, Fabrício Ferraz, Gerdes, Kim, Ginter, Filip, Godoy, Gustavo, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Huber, Eva, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Ito, Kaoru, Jelínek, Tomáš, Jha, Apoorva, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, K, Sarveswaran, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Kara, Neslihan, Katz, Boris, Kayadelen, Tolga, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kuyrukçu, Oğuzhan, Kuzgun, Aslı, Kwak, Sookyoung, Laippala, Veronika, Lam, Lucia, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yuan, Lim, KyungTae, Lima Padovani, Bruna, Lindén, Krister, Ljubešić, Nikola, Loginova, Olga, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Marşan, Büşra, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Martínez Alonso, Héctor, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, Mazzei, Alessandro, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Miekka, Niko, Mischenkova, Karina, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Molnár, Judit, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Moretti, Giovanni, Mori, Keiko Sophie, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nevaci, Manuela, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özçelik, Merve, Özgür, Arzucan, Öztürk Başaran, Balkız, Park, Hyunji Hayley, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Phelan, Jason, Piitulainen, Jussi, Pirinen, Tommi A, Pitler, Emily, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Rama, Taraka, Ramasamy, Loganathan, Ramisch, Carlos, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rocha, Luisa, Rögnvaldsson, Eiríkur, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sagot, Benoît, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Sanıyar, Ezgi, Särg, Dage, Saulīte, Baiba, Sawanakunanon, Yanin, Saxena, Shefali, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Schwartz, Lane, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shishkina, Yana, Shohibussirri, Muh, Sichinava, Dmitry, Siewert, Janine, Sigurðsson, Einar Freyr, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Simov, Kiril, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Spadine, Carolyn, Sprugnoli, Rachele, Steingrímsson, Steinþór, Stella, Antonio, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Szántó, Zsolt, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tella, Samson, Tellier, Isabelle, Testori, Marinella, Thomas, Guillaume, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vajjala, Sowmya, van der Goot, Rob, Vanhove, Martine, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Villemonte de la Clergerie, Eric, Vincze, Veronika, Vlasova, Natalia, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yenice, Arife Betül, Yıldız, Olcay Taner, Yu, Zhuoran, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhu, Hanzhi, Zhuravleva, Anna, and Ziane, Rayan
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, Tupinambá, Beja, Western Frisian, Guajajára, Urubú-Kaapor, Kangri, K'iche', Low German, Makuráp, Central Siberian Yupik, and Western Armenian
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008).
Rights:: Licence Universal Dependencies v2.8, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.8, and PUB

80. Universal Dependencies 2.8.1

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranzabe, Maria Jesus, Arıcan, Bilge Nas, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Aslan, Deniz Baran, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Barkarson, Starkaður, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Bengoetxea, Kepa, Berk, Gözde, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Braggaar, Anouck, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cassidy, Lauren, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cesur, Neslihan, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chauhan, Shweta, Chi, Ethan, Chika, Taishi, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Courtin, Marine, Cristescu, Mihaela, Daniel, Philemon., Davidson, Elizabeth, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Di Nuovo, Elisa, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Eckhoff, Hanne, Eiche, Sandra, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Fernanda, Marília, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerardi, Fabrício Ferraz, Gerdes, Kim, Ginter, Filip, Godoy, Gustavo, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Huber, Eva, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Ito, Kaoru, Jelínek, Tomáš, Jha, Apoorva, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, K, Sarveswaran, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Kara, Neslihan, Katz, Boris, Kayadelen, Tolga, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kuyrukçu, Oğuzhan, Kuzgun, Aslı, Kwak, Sookyoung, Laippala, Veronika, Lam, Lucia, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yuan, Lim, KyungTae, Lima Padovani, Bruna, Lindén, Krister, Ljubešić, Nikola, Loginova, Olga, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Marşan, Büşra, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Martínez Alonso, Héctor, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, Mazzei, Alessandro, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Miekka, Niko, Mischenkova, Karina, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Molnár, Judit, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Moretti, Giovanni, Mori, Keiko Sophie, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nevaci, Manuela, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özçelik, Merve, Özgür, Arzucan, Öztürk Başaran, Balkız, Park, Hyunji Hayley, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Phelan, Jason, Piitulainen, Jussi, Pirinen, Tommi A, Pitler, Emily, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Rama, Taraka, Ramasamy, Loganathan, Ramisch, Carlos, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rocha, Luisa, Rögnvaldsson, Eiríkur, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sagot, Benoît, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Sanıyar, Ezgi, Särg, Dage, Saulīte, Baiba, Sawanakunanon, Yanin, Saxena, Shefali, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Schwartz, Lane, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shishkina, Yana, Shohibussirri, Muh, Sichinava, Dmitry, Siewert, Janine, Sigurðsson, Einar Freyr, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Simov, Kiril, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Spadine, Carolyn, Sprugnoli, Rachele, Steingrímsson, Steinþór, Stella, Antonio, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Szántó, Zsolt, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tella, Samson, Tellier, Isabelle, Testori, Marinella, Thomas, Guillaume, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vajjala, Sowmya, van der Goot, Rob, Vanhove, Martine, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Villemonte de la Clergerie, Eric, Vincze, Veronika, Vlasova, Natalia, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yenice, Arife Betül, Yıldız, Olcay Taner, Yu, Zhuoran, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhu, Hanzhi, Zhuravleva, Anna, and Ziane, Rayan
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, Tupinambá, Beja, Western Frisian, Guajajára, Urubú-Kaapor, Kangri, K'iche', Low German, Makuráp, Central Siberian Yupik, and Western Armenian
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). Version 2.8.1 fixes a bug in 2.8 where a portion of the Dutch Alpino treebank was accidentally omitted.
Rights:: Licence Universal Dependencies v2.8, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.8, and PUB

81. Universal Dependencies 2.9

Creator:: Zeman, Daniel, Nivre, Joakim, Abrams, Mitchell, Ackermann, Elia, Aepli, Noëmi, Aghaei, Hamid, Agić, Željko, Ahmadi, Amir, Ahrenberg, Lars, Ajede, Chika Kennedy, Aleksandravičiūtė, Gabrielė, Alfina, Ika, Antonsen, Lene, Aplonova, Katya, Aquino, Angelina, Aragon, Carolina, Aranzabe, Maria Jesus, Arıcan, Bilge Nas, Arnardóttir, Þórunn, Arutie, Gashaw, Arwidarasti, Jessica Naraiswari, Asahara, Masayuki, Aslan, Deniz Baran, Ateyah, Luma, Atmaca, Furkan, Attia, Mohammed, Atutxa, Aitziber, Augustinus, Liesbeth, Badmaeva, Elena, Balasubramani, Keerthana, Ballesteros, Miguel, Banerjee, Esha, Bank, Sebastian, Barbu Mititelu, Verginica, Barkarson, Starkaður, Basile, Rodolfo, Basmov, Victoria, Batchelor, Colin, Bauer, John, Bedir, Seyyit Talha, Bengoetxea, Kepa, Berk, Gözde, Berzak, Yevgeni, Bhat, Irshad Ahmad, Bhat, Riyaz Ahmad, Biagetti, Erica, Bick, Eckhard, Bielinskienė, Agnė, Bjarnadóttir, Kristín, Blokland, Rogier, Bobicev, Victoria, Boizou, Loïc, Borges Völker, Emanuel, Börstell, Carl, Bosco, Cristina, Bouma, Gosse, Bowman, Sam, Boyd, Adriane, Braggaar, Anouck, Brokaitė, Kristina, Burchardt, Aljoscha, Candito, Marie, Caron, Bernard, Caron, Gauthier, Cassidy, Lauren, Cavalcanti, Tatiana, Cebiroğlu Eryiğit, Gülşen, Cecchini, Flavio Massimiliano, Celano, Giuseppe G. A., Čéplö, Slavomír, Cesur, Neslihan, Cetin, Savas, Çetinoğlu, Özlem, Chalub, Fabricio, Chauhan, Shweta, Chi, Ethan, Chika, Taishi, Cho, Yongseok, Choi, Jinho, Chun, Jayeol, Chung, Juyeon, Cignarella, Alessandra T., Cinková, Silvie, Collomb, Aurélie, Çöltekin, Çağrı, Connor, Miriam, Courtin, Marine, Cristescu, Mihaela, Daniel, Philemon, Davidson, Elizabeth, de Marneffe, Marie-Catherine, de Paiva, Valeria, Derin, Mehmet Oguz, de Souza, Elvis, Diaz de Ilarraza, Arantza, Dickerson, Carly, Dinakaramani, Arawinda, Di Nuovo, Elisa, Dione, Bamba, Dirix, Peter, Dobrovoljc, Kaja, Dozat, Timothy, Droganova, Kira, Dwivedi, Puneet, Eckhoff, Hanne, Eiche, Sandra, Eli, Marhaba, Elkahky, Ali, Ephrem, Binyam, Erina, Olga, Erjavec, Tomaž, Etienne, Aline, Evelyn, Wograine, Facundes, Sidney, Farkas, Richárd, Ferdaousi, Jannatul, Fernanda, Marília, Fernandez Alcalde, Hector, Foster, Jennifer, Freitas, Cláudia, Fujita, Kazunori, Gajdošová, Katarína, Galbraith, Daniel, Garcia, Marcos, Gärdenfors, Moa, Garza, Sebastian, Gerardi, Fabrício Ferraz, Gerdes, Kim, Ginter, Filip, Godoy, Gustavo, Goenaga, Iakes, Gojenola, Koldo, Gökırmak, Memduh, Goldberg, Yoav, Gómez Guinovart, Xavier, González Saavedra, Berta, Griciūtė, Bernadeta, Grioni, Matias, Grobol, Loïc, Grūzītis, Normunds, Guillaume, Bruno, Guillot-Barbance, Céline, Güngör, Tunga, Habash, Nizar, Hafsteinsson, Hinrik, Hajič, Jan, Hajič jr., Jan, Hämäläinen, Mika, Hà Mỹ, Linh, Han, Na-Rae, Hanifmuti, Muhammad Yudistira, Hardwick, Sam, Harris, Kim, Haug, Dag, Heinecke, Johannes, Hellwig, Oliver, Hennig, Felix, Hladká, Barbora, Hlaváčová, Jaroslava, Hociung, Florinel, Hohle, Petter, Huber, Eva, Hwang, Jena, Ikeda, Takumi, Ingason, Anton Karl, Ion, Radu, Irimia, Elena, Ishola, Ọlájídé, Ito, Kaoru, Jannat, Siratun, Jelínek, Tomáš, Jha, Apoorva, Johannsen, Anders, Jónsdóttir, Hildur, Jørgensen, Fredrik, Juutinen, Markus, K, Sarveswaran, Kaşıkara, Hüner, Kaasen, Andre, Kabaeva, Nadezhda, Kahane, Sylvain, Kanayama, Hiroshi, Kanerva, Jenna, Kara, Neslihan, Katz, Boris, Kayadelen, Tolga, Kenney, Jessica, Kettnerová, Václava, Kirchner, Jesse, Klementieva, Elena, Klyachko, Elena, Köhn, Arne, Köksal, Abdullatif, Kopacewicz, Kamil, Korkiakangas, Timo, Köse, Mehmet, Kotsyba, Natalia, Kovalevskaitė, Jolanta, Krek, Simon, Krishnamurthy, Parameswari, Kübler, Sandra, Kuyrukçu, Oğuzhan, Kuzgun, Aslı, Kwak, Sookyoung, Laippala, Veronika, Lam, Lucia, Lambertino, Lorenzo, Lando, Tatiana, Larasati, Septina Dian, Lavrentiev, Alexei, Lee, John, Lê Hồng, Phương, Lenci, Alessandro, Lertpradit, Saran, Leung, Herman, Levina, Maria, Li, Cheuk Ying, Li, Josie, Li, Keying, Li, Yuan, Lim, KyungTae, Lima Padovani, Bruna, Lindén, Krister, Ljubešić, Nikola, Loginova, Olga, Lusito, Stefano, Luthfi, Andry, Luukko, Mikko, Lyashevskaya, Olga, Lynn, Teresa, Macketanz, Vivien, Mahamdi, Menel, Maillard, Jean, Makazhanov, Aibek, Mandl, Michael, Manning, Christopher, Manurung, Ruli, Marşan, Büşra, Mărănduc, Cătălina, Mareček, David, Marheinecke, Katrin, Martínez Alonso, Héctor, Martín-Rodríguez, Lorena, Martins, André, Mašek, Jan, Matsuda, Hiroshi, Matsumoto, Yuji, Mazzei, Alessandro, McDonald, Ryan, McGuinness, Sarah, Mendonça, Gustavo, Merzhevich, Tatiana, Miekka, Niko, Mischenkova, Karina, Misirpashayeva, Margarita, Missilä, Anna, Mititelu, Cătălin, Mitrofan, Maria, Miyao, Yusuke, Mojiri Foroushani, AmirHossein, Molnár, Judit, Moloodi, Amirsaeid, Montemagni, Simonetta, More, Amir, Moreno Romero, Laura, Moretti, Giovanni, Mori, Keiko Sophie, Mori, Shinsuke, Morioka, Tomohiko, Moro, Shigeki, Mortensen, Bjartur, Moskalevskyi, Bohdan, Muischnek, Kadri, Munro, Robert, Murawaki, Yugo, Müürisep, Kaili, Nainwani, Pinkey, Nakhlé, Mariam, Navarro Horñiacek, Juan Ignacio, Nedoluzhko, Anna, Nešpore-Bērzkalne, Gunta, Nevaci, Manuela, Nguyễn Thị, Lương, Nguyễn Thị Minh, Huyền, Nikaido, Yoshihiro, Nikolaev, Vitaly, Nitisaroj, Rattima, Nourian, Alireza, Nurmi, Hanna, Ojala, Stina, Ojha, Atul Kr., Olúòkun, Adédayọ̀, Omura, Mai, Onwuegbuzia, Emeka, Osenova, Petya, Östling, Robert, Øvrelid, Lilja, Özateş, Şaziye Betül, Özçelik, Merve, Özgür, Arzucan, Öztürk Başaran, Balkız, Park, Hyunji Hayley, Partanen, Niko, Pascual, Elena, Passarotti, Marco, Patejuk, Agnieszka, Paulino-Passos, Guilherme, Peljak-Łapińska, Angelika, Peng, Siyao, Perez, Cenel-Augusto, Perkova, Natalia, Perrier, Guy, Petrov, Slav, Petrova, Daria, Phelan, Jason, Piitulainen, Jussi, Pirinen, Tommi A, Pitler, Emily, Plank, Barbara, Poibeau, Thierry, Ponomareva, Larisa, Popel, Martin, Pretkalniņa, Lauma, Prévost, Sophie, Prokopidis, Prokopis, Przepiórkowski, Adam, Puolakainen, Tiina, Pyysalo, Sampo, Qi, Peng, Rääbis, Andriela, Rademaker, Alexandre, Rahoman, Mizanur, Rama, Taraka, Ramasamy, Loganathan, Ramisch, Carlos, Rashel, Fam, Rasooli, Mohammad Sadegh, Ravishankar, Vinit, Real, Livy, Rebeja, Petru, Reddy, Siva, Regnault, Mathilde, Rehm, Georg, Riabov, Ivan, Rießler, Michael, Rimkutė, Erika, Rinaldi, Larissa, Rituma, Laura, Rizqiyah, Putri, Rocha, Luisa, Rögnvaldsson, Eiríkur, Romanenko, Mykhailo, Rosa, Rudolf, Roșca, Valentin, Rovati, Davide, Rudina, Olga, Rueter, Jack, Rúnarsson, Kristján, Sadde, Shoval, Safari, Pegah, Sagot, Benoît, Sahala, Aleksi, Saleh, Shadi, Salomoni, Alessio, Samardžić, Tanja, Samson, Stephanie, Sanguinetti, Manuela, Sanıyar, Ezgi, Särg, Dage, Saulīte, Baiba, Sawanakunanon, Yanin, Saxena, Shefali, Scannell, Kevin, Scarlata, Salvatore, Schneider, Nathan, Schuster, Sebastian, Schwartz, Lane, Seddah, Djamé, Seeker, Wolfgang, Seraji, Mojgan, Shahzadi, Syeda, Shen, Mo, Shimada, Atsuko, Shirasu, Hiroyuki, Shishkina, Yana, Shohibussirri, Muh, Sichinava, Dmitry, Siewert, Janine, Sigurðsson, Einar Freyr, Silveira, Aline, Silveira, Natalia, Simi, Maria, Simionescu, Radu, Simkó, Katalin, Šimková, Mária, Simov, Kiril, Skachedubova, Maria, Smith, Aaron, Soares-Bastos, Isabela, Sourov, Shafi, Spadine, Carolyn, Sprugnoli, Rachele, Steingrímsson, Steinþór, Stella, Antonio, Straka, Milan, Strickland, Emmett, Strnadová, Jana, Suhr, Alane, Sulestio, Yogi Lesmana, Sulubacak, Umut, Suzuki, Shingo, Szántó, Zsolt, Taguchi, Chihiro, Taji, Dima, Takahashi, Yuta, Tamburini, Fabio, Tan, Mary Ann C., Tanaka, Takaaki, Tanaya, Dipta, Tella, Samson, Tellier, Isabelle, Testori, Marinella, Thomas, Guillaume, Torga, Liisi, Toska, Marsida, Trosterud, Trond, Trukhina, Anna, Tsarfaty, Reut, Türk, Utku, Tyers, Francis, Uematsu, Sumire, Untilov, Roman, Urešová, Zdeňka, Uria, Larraitz, Uszkoreit, Hans, Utka, Andrius, Vajjala, Sowmya, van der Goot, Rob, Vanhove, Martine, van Niekerk, Daniel, van Noord, Gertjan, Varga, Viktor, Villemonte de la Clergerie, Eric, Vincze, Veronika, Vlasova, Natalia, Wakasa, Aya, Wallenberg, Joel C., Wallin, Lars, Walsh, Abigail, Wang, Jing Xian, Washington, Jonathan North, Wendt, Maximilan, Widmer, Paul, Wijono, Sri Hartati, Williams, Seyi, Wirén, Mats, Wittern, Christian, Woldemariam, Tsegay, Wong, Tak-sum, Wróblewska, Alina, Yako, Mary, Yamashita, Kayo, Yamazaki, Naoki, Yan, Chunxiao, Yasuoka, Koichi, Yavrumyan, Marat M., Yenice, Arife Betül, Yıldız, Olcay Taner, Yu, Zhuoran, Yuliawati, Arlisa, Žabokrtský, Zdeněk, Zahra, Shorouq, Zeldes, Amir, Zhou, He, Zhu, Hanzhi, Zhuravleva, Anna, and Ziane, Rayan
Publisher:: Universal Dependencies Consortium
Type:: text and corpus
Subject:: treebank, dependency, syntax, morphology, harmonized annotation, interset, universal tagset, and stanford dependencies
Language:: Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, Maltese, Welsh, Wolof, Assyrian Neo-Aramaic, Literary Chinese, Old Russian, Karelian, Mbyá Guaraní, Bhojpuri, Komi-Permyak, Livvi, Moksha, Scottish Gaelic, Skolt Sami, Swiss German, Albanian, Icelandic, Akuntsu, Apurinã, Chukot, Khunsari, Manx, Mundurukú, Nayini, Old Turkish, Soi, South Levantine Arabic, Tupinambá, Beja, Western Frisian, Guajajára, Urubú-Kaapor, Kangri, K'iche', Low German, Makuráp, Central Siberian Yupik, Western Armenian, Bengali, Javanese, Karo (Brazil), Ligurian, Neapolitan, Tatar, Xibe, and Yakut
Description:: Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). Version 2.8.1 fixes a bug in 2.8 where a portion of the Dutch Alpino treebank was accidentally omitted.
Rights:: Licence Universal Dependencies v2.9, https://lindat.mff.cuni.cz/repository/xmlui/page/license-ud-2.9, and PUB

82. Universal Derivations v0.5

Creator:: Kyjánek, Lukáš, Žabokrtský, Zdeněk, Vidra, Jonáš, and Ševčíková, Magda
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: universal derivations, uder, word-formation, derivation, derivational morphology, and lexical network
Language:: Czech, English, Estonian, Finnish, French, German, Latin, Persian, Polish, Portuguese, and Spanish
Description:: Universal Derivations (UDer) is a collection of harmonized lexical networks capturing word-formation, especially derivational relations, in a cross-linguistically consistent annotation scheme for many languages. The annotation scheme is based on a rooted tree data structure, in which nodes correspond to lexemes, while edges represent derivational relations or compounding. The current version of the UDer collection contains eleven harmonized resources covering eleven different languages.
Rights:: Universal Derivations v0.5 License Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UDer-0.5, and PUB

83. Universal Derivations v1.0

Creator:: Kyjánek, Lukáš, Žabokrtský, Zdeněk, Vidra, Jonáš, and Ševčíková, Magda
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: universal derivations, uder, word-formation, derivation, derivational morphology, lexical network, and harmonization
Language:: Czech, English, Estonian, Finnish, German, French, Latin, Persian, Polish, Portuguese, Spanish, Catalan, Turkish, Scottish Gaelic, Russian, Swedish, Serbo-Croatian, Italian, Dutch, and Croatian
Description:: Universal Derivations (UDer) is a collection of harmonized lexical networks capturing word-formation, especially derivational relations, in a cross-linguistically consistent annotation scheme for many languages. The annotation scheme is based on a rooted tree data structure, in which nodes correspond to lexemes, while edges represent derivational relations or compounding. The current version of the UDer collection contains twenty-seven harmonized resources covering twenty different languages.
Rights:: Universal Derivations v1.0 License Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UDer-1.0, and PUB

84. Universal Derivations v1.1

Creator:: Kyjánek, Lukáš, Žabokrtský, Zdeněk, Vidra, Jonáš, and Ševčíková, Magda
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: lexicon, text, and lexicalConceptualResource
Subject:: universal derivations, uder, word-formation, derivation, derivational morphology, lexical network, and harmonization
Language:: Czech, English, Estonian, Finnish, German, French, Latin, Persian, Polish, Portuguese, Spanish, Catalan, Turkish, Scottish Gaelic, Russian, Swedish, Serbo-Croatian, Italian, Dutch, Croatian, and Slovenian
Description:: Universal Derivations (UDer) is a collection of harmonized lexical networks capturing word-formation, especially derivational relations, in a cross-linguistically consistent annotation scheme for many languages. The annotation scheme is based on a rooted tree data structure, in which nodes correspond to lexemes, while edges represent derivational relations or compounding. The current version of the UDer collection contains thirty-one harmonized resources covering twenty-one different languages.
Rights:: Universal Derivations v1.1 License Agreement, PUB, and https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UDer-1.1

85. Universal Segmentations 1.0 (UniSegments 1.0)

Creator:: Žabokrtský, Zdeněk, Bafna, Nyati, Bodnár, Jan, Kyjánek, Lukáš, Svoboda, Emil, Ševčíková, Magda, Vidra, Jonáš, Angle, Sachi, Ansari, Ebrahim, Arkhangelskiy, Timofey, Batsuren, Khuyagbaatar, Bella, Gábor, Bertinetto, Pier Marco, Bonami, Olivier, Celata, Chiara, Daniel, Michael, Fedorenko, Alexei, Filko, Matea, Giunchiglia, Fausto, Haghdoost, Hamid, Hathout, Nabil, Khomchenkova, Irina, Khurshudyan, Victoria, Levonian, Dmitri, Litta, Eleonora, Medvedeva, Maria, Muralikrishna, S. N., Namer, Fiammetta, Nikravesh, Mahshid, Padó, Sebastian, Passarotti, Marco, Plungian, Vladimir, Polyakov, Alexey, Potapov, Mihail, Pruthwik, Mishra, Rao B, Ashwath, Rubakov, Sergei, Samar, Husain, Sharma, Dipti Misra, Šnajder, Jan, Šojat, Krešimir, Štefanec, Vanja, Talamo, Luigi, Tribout, Delphine, Vodolazsky, Daniil, Vydrin, Arseniy, Zakirova, Aigul, and Zeller, Britta
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: universal segmentations, morphological segmentation, word segmentation, segmentation, morphology, morphemes, morphological dictionary, unisegments, morph, and multilingual
Language:: Czech, Catalan, German, English, Persian, Finnish, French, Serbo-Croatian, Croatian, Hungarian, Italian, Komi-Zyrian, Latin, Moksha, Mari (Russia), Mongolian, Erzya, Polish, Portuguese, Russian, Spanish, Swedish, Tajik, Udmurt, Armenian, Bengali, Hindi, Malayalam, Marathi, and Kannada
Description:: Universal Segmentations (UniSegments) is a collection of lexical resources capturing morphological segmentations harmonised into a cross-linguistically consistent annotation scheme for many languages. The annotation scheme consists of simple tab-separated columns that stores a word and its morphological segmentations, including pieces of information about the word and the segmented units, e.g., part-of-speech categories, type of morphs/morphemes etc. The current public version of the collection contains 38 harmonised segmentation datasets covering 30 different languages.
Rights:: Universal Segmentations 1.0 License Terms, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-unisegs-1.0, and PUB

86. VALLEX 4.0 (2021-02-12)

Creator:: Lopatková, Markéta, Kettnerová, Václava, Vernerová, Anna, Bejček, Eduard, and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, valency, Czech, and lexicon
Language:: Czech
Description:: VALLEX 4.0 provides information on the valency structure (combinatorial potential) of verbs in their particular senses; each sense is by a gloss and examples. VALLEX 4.0 describes almost 4 700 Czech verbs in more than 11 000 lexical units, i.e., given verbs in the given senses. VALLEX 4.0 is a is a collection of linguistically annotated data and documentation, resulting from an attempt at formal description of valency frames of Czech verbs. In order to satisfy different needs of different potential users, the lexicon is distributed (i) in a HTML version (the data allows for an easy and fast navigation through the lexicon) and (ii) in a machine-tractable form, so that the VALLEX data can be used in NLP applications. VALLEX 4.0 provides (in addition to information from previous versions) also characteristics of verbs expressing reciprocity and reflexivity. The data is provided in two formats: XML and JSON.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

87. VALLEX 4.5

Creator:: Lopatková, Markéta, Kettnerová, Václava, Mírovský, Jiří, Vernerová, Anna, Bejček, Eduard, and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, lexicon, and lexicalConceptualResource
Subject:: verbal valency, valency, Czech, and lexicon
Language:: Czech
Description:: VALLEX 4.5 provides information on the valency structure (combinatorial potential) of Czech verbs in their particular senses (almost 4 700 verbs in more than 11 080 lexical units, supplemented with more than 290 nouns in more than 350 lexical units forming complex predicates with light verbs). VALLEX 4.5 is an enhanced successor of VALLEX 3.0, 3.5, and 4.0. In addition to the information stored there, VALLEX 4.5 provides a detailed description of reflexive verbs, i.e., verbs with the reflexive "se" or "si" as an obligatory part of their verb lexemes. VALLEX 4.5 covers 1 525 reflexive verbs in 1 545 lexical units (2 501 when aspectual counterparts counted separately). In order to satisfy different needs of different potential users, the lexicon is distributed (i) online in a HTML version (the data allows for an easy and fast navigation through the lexicon) and (ii) in this distribution in a machine-tractable form, so that the VALLEX data can be used in NLP applications.
Rights:: Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

Search

Search Constraints

Search Results

Limit your search

Contributor

Show values starting with

Creator

Show values starting with

Language

Show values starting with

Publisher

Show values starting with

Rights

Show values starting with

Subject

Show values starting with

Type

Show values starting with

Date

Original context has metadata only

Harvested from