Rights: PUB - LINDAT/CLARIAH-CZ Catalog Search Results

1. A Gold Standard Word Alignment for English-Swedish (2015-10-12)

Creator:: Ahrenberg, Lars and Holmqvist, Maria
Publisher:: Linköping University
Type:: text, wordList, and lexicalConceptualResource
Subject:: word alignment
Language:: Swedish and English
Description:: A Gold Standard Word Alignment for English-Swedish (GES) is a resource containing 1164 manually word aligned sentences pairs from English and Swedish versions of Europarl v. 2.
Rights:: Creative Commons - Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), http://creativecommons.org/licenses/by-nc/4.0/, and PUB

2. 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

3. 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

4. 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

5. 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

6. A morphological layer for the German part of the SMULTRON corpus

Creator:: Müller, Thomas, Schütze, Hinrich, Caratti, Francesca, and Recknagel, Arne
Publisher:: Center for Information and Language Processing, University of Munich
Type:: text and corpus
Subject:: morphology, morphological tagging, and PoS tagging
Language:: German
Description:: A morphological layer for the German part of the SMULTRON corpus. Layer was annotated according to the STTS tagset and the annotation guidelines of the Tiger corpus. Coordinator: Thomas Müller Annotators: Francesca Caratti, Arne Recknagel This distribution contains a morphological layer for the SMULTRON corpus [0]. The annotation process is described in : @InProceedings{mueller2015, author = {M\"uller, Thomas and Sch\"utze, Hinrich}, title = {Robust Morphological Tagging with Word Representations}, booktitle = {Proceedings of NAACL}, year = {2015}, } [0] http://www.cl.uzh.ch/research/parallelcorpora/paralleltreebanks/smultron_en.html
Rights:: Creative Commons - Attribution 3.0 Unported (CC BY 3.0), http://creativecommons.org/licenses/by/3.0/, and PUB

7. A Small Dataset for English-to-Czech Speech Translation in the Travel Domain

Creator:: Cífka, Ondřej and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: audio and corpus
Subject:: speech corpus, ASR, and machine translation
Language:: English and Czech
Description:: This small dataset contains 3 speech corpora collected using the Alex Translate telephone service (https://ufal.mff.cuni.cz/alex#alex-translate). The "part1" and "part2" corpora contain English speech with transcriptions and Czech translations. These recordings were collected from users of the service. Part 1 contains earlier recordings, filtered to include only clean speech; Part 2 contains later recordings with no filtering applied. The "cstest" corpus contains recordings of artificially created sentences, each containing one or more Czech names of places in the Czech Republic. These were recorded by a multinational group of students studying in Prague.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB

8. A Speech Test Set of Practice Business Presentations with Additional Relevant Texts

Creator:: Macháček, Dominik, Kratochvíl, Jonáš, Vojtěchová, Tereza, and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: audio and corpus
Subject:: ASR, ASR evaluation, speech corpus, non-native English, speech recognition, speech recognition evaluation, speech and relevant texts, and European non-native English
Language:: English
Description:: We present a test corpus of audio recordings and transcriptions of presentations of students' enterprises together with their slides and web-pages. The corpus is intended for evaluation of automatic speech recognition (ASR) systems, especially in conditions where the prior availability of in-domain vocabulary and named entities is benefitable. The corpus consists of 39 presentations in English, each up to 90 seconds long, and slides and web-pages in Czech, Slovak, English, German, Romanian, Italian or Spanish. The speakers are high school students from European countries with English as their second language. We benchmark three baseline ASR systems on the corpus and show their imperfection.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

9. Additional German-Czech reference translations of the WMT'11 test set

Creator:: Bojar, Ondřej, Zeman, Daniel, Dušek, Ondřej, Břečková, Jana, Farkačová, Hana, Grošpic, Pavel, Kačenová, Kristýna, Knechtová, Eva, Koubová, Anna, Lukavská, Jana, Nováková, Petra, and Petrdlíková, Jana
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: reference translation, German-Czech, and parallel corpus
Language:: German and Czech
Description:: Additional three Czech reference translations of the whole WMT 2011 data set (http://www.statmt.org/wmt11/test.tgz), translated from the German originals. Original segmentation of the WMT 2011 data is preserved. and This project has been sponsored by the grants GAČR P406/11/1499 and EuroMatrixPlus (FP7-ICT-2007-3-231720 of the EU and 7E09003+7E11051 of the Ministry of Education, Youth and Sports of the Czech Republic)
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

10. Addressed Arabic Phonetic Rules

Creator:: Mustafa, Ebtihal and Bouzoubaa, Karim
Publisher:: languages journal
Type:: text, wordList, and lexicalConceptualResource
Subject:: phonetics and Arabic phonetic System.
Language:: Arabic
Description:: This xml file describes the Arabic phonetic constraints are to be applied on Arabic root. The first rule category lists the letters that may not occur in the same root, regardless of their order. The second category lists the letters that may not be used together in a root word with a specific order. The third and fourth categories show that each contiguous letters must not be redundant ISLRN: 991-445-325-823-5
Rights:: Creative Commons - Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), http://creativecommons.org/licenses/by-nc/4.0/, and PUB

11. AdjDeriNet: Words Derived from Adjectives in Czech

Creator:: Ševčíková, Magda and Žabokrtský, Zdeněk
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, wordList, and lexicalConceptualResource
Subject:: adjectives, derivation, word-formation, and derivational morphology
Language:: Czech
Description:: Lexical network AdjDeriNet consists of pairs of base adjectives and their derivatives. It contains nearly 18 thousand base adjectives that are base words for more than 26 thousand lexemes of several parts of speech.
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. Air Traffic Control Communication

Creator:: Šmídl, Luboš
Publisher:: University of West Bohemia, Department of Cybernetics
Type:: audio and corpus
Subject:: speech corpus and acoustic model
Language:: English
Description:: Corpus contains recordings of communication between air traffic controllers and pilots. The speech is manually transcribed and labeled with the information about the speaker (pilot/controller, not the full identity of the person). The corpus is currently small (20 hours) but we plan to search for additional data next year. The audio data format is: 8kHz, 16bit PCM, mono. and Technology Agency of the Czech Republic, project No. TA01030476.
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

13. AKCES 1

Creator:: Šebesta, Karel, Goláňová, Hana, Letafková, Jana, and Jelínková, Blanka
Publisher:: Charles University in Prague, ÚČJTK
Type:: text and corpus
Subject:: youth language and written language
Language:: Czech
Description:: Corpus AKCES 1 includes texts written in czech by youth (native speakers); it is the same data as the corpus SKRIPT 2012
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

14. AKCES 2

Creator:: Šebesta, Karel and Goláňová, Hana
Publisher:: Charles University in Prague, ÚČJTK
Type:: text and corpus
Subject:: youth language, classroom, language acquisition corpus, and AKCES
Language:: Czech
Description:: Corpus AKCES 2 consists of trancripts of recordings of classes at Czech elementary and secondary schools (AKCES/CLAC - Czech Language Acquisition Corpora). It is the same data as the corpus "Schola 2010" (see the link for search), but all the proper names have been removed in order to protect the privacy of participants. and MŠMT (MSM0021620825), UK (PRVOUK P 10)
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

15. AKCES 2 ver. 2

Creator:: Šebesta, Karel and Goláňová, Hana
Publisher:: Charles University in Prague, ÚČJTK
Type:: text and corpus
Subject:: youth language, classroom, language acquisition corpus, and AKCES
Language:: Czech
Description:: Corpus AKCES 2 ver. 2 consists of full, unabridged trancripts of recordings of classes at Czech elementary and secondary schools (AKCES/CLAC - Czech Language Acquisition Corpora). It is the same data as the corpus "Schola 2010" (see the link for search), but all the proper names have been removed in order to protect the privacy of participants. and UK, PRVOUK P10
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

16. AKCES 3

Creator:: Šebesta, Karel, Bedřichová, Zuzanna, Šormová, Kateřina, Štindlová, Barbora, Hrdlička, Milan, Hrdličková, Tereza, Hana, Jiří, Rosen, Alexandr, Petkevič, Vladimír, Jelínek, Tomáš, Škodová, Svatava, Poláčková, Marie, Janeš, Petr, Lundáková, Kateřina, Skoumalová, Hana, Šťastný, Klement, Sládek, Šimon, and Pierscieniak, Piotr
Publisher:: Charles University in Prague, ÚČJTK
Type:: text and corpus
Subject:: Czech as a foreign language, Czech language acquisition corpora, non-native speakers, AKCES, and second language aquisition
Language:: Czech
Description:: Corpus AKCES 3 includes texts written in czech by non-native speakers (AKCES/CLAC - Czech Language Acquisition Corpora) and ESF (OPVK CZ.1.07/2.2.00/07.0259), MŠMT (MSM0021620825), UK (P10)
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

17. AKCES 4

Creator:: Šebesta, Karel, Bedřichová, Zuzanna, Štindlová, Barbora, Hrdlička, Milan, Hrdličková, Tereza, Hana, Jiří, Rosen, Alexandr, Petkevič, Vladimír, Jelínek, Tomáš, Škodová, Svatava, Janeš, Petr, Lundáková, Kateřina, Skoumalová, Hana, Šťastný, Klement, and Sládek, Šimon
Publisher:: Charles University
Type:: text and corpus
Subject:: language of children, Czech language acquisition, adolescents, and AKCES
Language:: Czech
Description:: Corpus AKCES 4 includes texts written in czech by youth growing up in locations at risk of social exclusion (AKCES/CLAC - Czech Language Acquisition Corpora) and ESF (OPVK CZ.1.07/2.2.00/07.0259), MŠMT (MSM0021620825), UK (P10)
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

18. AKCES 5 (CzeSL-SGT)

Creator:: Šebesta, Karel, Bedřichová, Zuzanna, Šormová, Kateřina, Štindlová, Barbora, Hrdlička, Milan, Hrdličková, Tereza, Hana, Jiří, Petkevič, Vladimír, Jelínek, Tomáš, Škodová, Svatava, Poláčková, Marie, Janeš, Petr, Lundáková, Kateřina, Skoumalová, Hana, Sládek, Šimon, Pierscieniak, Piotr, Toufarová, Dagmar, Richter, Michal, Straka, Milan, and Rosen, Alexandr
Publisher:: Charles University
Type:: text and corpus
Subject:: learner corpus, Czech as a foreign language, Czech language acquisition corpora, AKCES, non-native speakers, and second language aquisition
Language:: Czech
Description:: Essays written by non-native learners of Czech, a part of AKCES/CLAC – Czech Language Acquisition Corpora. CzeSL-SGT stands for Czech as a Second Language with Spelling, Grammar and Tags. Extends the “foreign” (ciz) part of AKCES 3 (CzeSL-plain) by texts collected in 2013. Original forms and automatic corrections are tagged, lemmatized and assigned erros labels. Most texts have metadata attributes (30 items) about the author and the text.
Rights:: Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0), http://creativecommons.org/licenses/by-sa/3.0/, and PUB

19. AKCES 5 (CzeSL-SGT) Release 2

Creator:: Šebesta, Karel, Bedřichová, Zuzanna, Šormová, Kateřina, Štindlová, Barbora, Hrdlička, Milan, Hrdličková, Tereza, Hana, Jiří, Petkevič, Vladimír, Jelínek, Tomáš, Škodová, Svatava, Poláčková, Marie, Janeš, Petr, Lundáková, Kateřina, Skoumalová, Hana, Sládek, Šimon, Pierscieniak, Piotr, Toufarová, Dagmar, Richter, Michal, Straka, Milan, and Rosen, Alexandr
Publisher:: Charles University
Type:: text and corpus
Subject:: learner corpus, Czech as a foreign language, Czech language acquisition corpora, AKCES, non-native speakers, and second language acquistion
Language:: Czech
Description:: Essays written by non-native learners of Czech, a part of AKCES/CLAC – Czech Language Acquisition Corpora. CzeSL-SGT stands for Czech as a Second Language with Spelling, Grammar and Tags. Extends the “foreign” (ciz) part of AKCES 3 (CzeSL-plain) by texts collected in 2013. Original forms and automatic corrections are tagged, lemmatized and assigned erros labels. Most texts have metadata attributes (30 items) about the author and the text. In addition to a few minor bugs, fixes a critical issue in Release 1: the native speakers of Ukrainian (s_L1:"uk") were wrongly labelled as speakers of "other European languages" (s_L1_group="IE"), instead of speakers of a Slavic language (s_L1_group="S"). The file is now a regular XML document, with all annotation represented as XML attributes.
Rights:: Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0), http://creativecommons.org/licenses/by-sa/3.0/, and PUB

20. AKCES-GEC Grammatical Error Correction Dataset for Czech

Creator:: Šebesta, Karel, Bedřichová, Zuzanna, Šormová, Kateřina, Štindlová, Barbora, Hrdlička, Milan, Hrdličková, Tereza, Hana, Jiří, Petkevič, Vladimír, Jelínek, Tomáš, Škodová, Svatava, Janeš, Petr, Lundáková, Kateřina, Skoumalová, Hana, Sládek, Šimon, Pierscieniak, Piotr, Toufarová, Dagmar, Straka, Milan, Rosen, Alexandr, Náplava, Jakub, and Poláčková, Marie
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: natural language correction, grammatical error correction, and gec
Language:: Czech
Description:: AKCES-GEC is a grammar error correction corpus for Czech generated from a subset of AKCES. It contains train, dev and test files annotated in M2 format. Note that in comparison to CZESL-GEC dataset, this dataset contains separated edits together with their type annotations in M2 format and also has two times more sentences. If you use this dataset, please use following citation: @article{naplava2019wnut, title={Grammatical Error Correction in Low-Resource Scenarios}, author={N{\'a}plava, Jakub and Straka, Milan}, journal={arXiv preprint arXiv:1910.00353}, year={2019} }
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. AlbMoRe Movie Reviews in Albanian

Creator:: Çano, Erion
Publisher:: University of Vienna
Type:: text and corpus
Subject:: sentiment analysis, under-resourced language, and albanian language
Language:: Albanian
Description:: AlbMoRe is a sentiment analysis corpus of movie reviews in Albanian, consisting of 800 records in CSV format. Each record includes a text review retrieved from IMDb and translated in Albanian by the author. It also contains a 0 negative) or 1 (positive) label added by the author. The corpus is fully balanced, consisting of 400 positive and 400 negative reviews about 67 movies of different genres. AlbMoRe corpus is released under CC-BY license (https://creativecommons.org/licenses/by/4.0/). If using the data, please cite the following paper: Çano Erion. AlbMoRe: A Corpus of Movie Reviews for Sentiment Analysis in Albanian. CoRR, abs/2306.08526, 2023. URL https://arxiv.org/abs/2306.08526.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), PUB, and http://creativecommons.org/licenses/by/4.0/

22. AlbNER Named Entity Recognition in Albanian

Creator:: Çano, Erion
Publisher:: University of Vienna
Type:: text and corpus
Subject:: named entity recognition, under-resourced languages, and albanian language
Language:: Albanian
Description:: AlbNER is a Named Entity Recognition corpus of Wikipedia sentences in Albanian, consisting of 900 records. The sentence tokens are manually labeled complying with the CoNLL-2003 shared task annotation scheme explained at https://aclanthology.org/W03-0419.pdf that uses I-ORG, B-ORG, I-PER, B-PER, I-LOC, B-LOC, I-MISC, B-MISC and O tags. AlbNER data are released under CC-BY license (https://creativecommons.org/licenses/by/4.0/). If using AlbMoRe corpus, please cite the following paper: Çano Erion. AlbNER: A Corpus for Named Entity Recognition in Albanian. CoRR, abs/2309.08741, 2023. URL https://arxiv.org/abs/2309.08741.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

23. AlbNews Albanian Topic Modeling

Creator:: Çano, Erion
Publisher:: University of Vienna
Type:: text and corpus
Subject:: under-resourced language, albanian language, and topic modeling
Language:: Albanian
Description:: AlbNews is a topic modeling corpus of news headlines in Albanian, consisting of 600 labeled samples and 2600 unlabeled samples. Each labeled sample includes a headline text retrieved from Albanian online news portals. It also contains one of the four labels: 'pol' for politics, 'cul' for culture, 'eco' for economy, and 'spo' for sport. Each of the unlabeled samples contain a headline text only.AlbTopic corpus is released under CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). If using the data, please cite the following paper: Çano Erion, Lamaj Dario. AlbNews: A Corpus of Headlines for Topic Modeling in Albanian. CoRR, abs/2402.04028, 2024. URL: https://arxiv.org/abs/2402.04028.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

24. Alex Context NLG Dataset

Creator:: Dušek, Ondřej and Jurčíček, Filip
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: dialogue system, natural language generation, dialogue alignment, and entrainment
Language:: English
Description:: A dataset intended for fully trainable natural language generation (NLG) systems in task-oriented spoken dialogue systems (SDS), covering the English public transport information domain. It includes preceding context (user utterance) along with each data instance (pair of source meaning representation and target natural language paraphrase to be generated). Taking the form of the previous user utterance into account for generating the system response allows NLG systems trained on this dataset to entrain (adapt) to the preceding utterance, i.e., reuse wording and syntactic structure. This should presumably improve the perceived naturalness of the output, and may even lead to a higher task success rate. Crowdsourcing has been used to obtain natural context user utterances as well as natural system responses to be generated.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB

25. 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

26. Annotated corpora and tools of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions (edition 1.0)

Creator:: Savary, Agata, Ramisch, Carlos, Cordeiro, Silvio Ricardo, Sangati, Federico, Vincze, Veronika, QasemiZadeh, Behrang, Candito, Marie, Cap, Fabienne, Giouli, Voula, Stoyanova, Ivelina, Doucet, Antoine, Adalı, Kübra, Barbu Mititelu, Verginica, Bejček, Eduard, El Maarouf, Ismail, Eryiğit, Gülşen, Galea, Luke, Ha-Cohen Kerner, Yaakov, Liebeskind, Chaya, Monti, Johanna, Parra Escartín, Carla, Kovalevskaitė, Jolanta, Krek, Simon, van der Plas, Lonneke, Aceta, Cristina, Aduriz, Itziar, Antoine, Jean-Yves, Attard, Greta, Azzopardi, Kirsty, Boizou, Loic, Bonnici, Janice, Boz, Mert, Bumbulienė, Ieva, Busuttil, Jael, Caruso, Valeria, Cherchi, Manuela, Constant, Matthieu, Czerepowicka, Monika, De Santis, Anna, Dimitrova, Tsvetana, Dinç, Tutkum, Elyovich, Hevi, Fabri, Ray, Farrugia, Alison, Findlay, Jamie, Fotopoulou, Aggeliki, Foufi, Vassiliki, Galea, Sara Anne, Gantar, Polona, Gatt, Albert, Gatt, Anabelle, Herrero, Carlos, Iñurrieta, Uxoa, Jagfeld, Glorianna, Hnátková, Milena, Ionescu, Mihaela, Klyueva, Natalia, Koeva, Svetla, Kovács, Viktória, Kuzman, Taja, Leseva, Svetlozara, Louisou, Sevi, Lynn, Teresa, Malka, Ruth, Martínez Alonso, Héctor, McCrae, John, de Medeiros Caseli, Helena, Miral, Ayşenur, Muscat, Amanda, Nivre, Joakim, Oakes, Michael, Onofrei, Mihaela, Parmentier, Yannick, Pasquer, Caroline, Pia di Buono, Maria, Priego Sanchez, Belem, Raffone, Annalisa, Ramisch, Renata, Rimkutė, Erika, Rizea, Monica-Mihaela, Simkó, Katalin, Spagnol, Michael, Stefanova, Valentina, Stymne, Sara, Sulubacak, Umut, Tabone, Nicole, Tanti, Marc, Todorova, Maria, Urešová, Zdenka, Villavicencio, Aline, and Zilio, Leonardo
Publisher:: PARSEME
Type:: text and corpus
Subject:: Multiword expressions, verbal multiword expressions, idioms, light-verb constructions, verb-particle constructions, and inherently reflexive verbs
Language:: Bulgarian, Czech, German, Modern Greek (1453-), Spanish, Persian, French, Hebrew, Hungarian, Italian, Lithuanian, Maltese, Polish, Portuguese, Romanian, Slovenian, Swedish, and Turkish
Description:: The PARSEME shared task aims at identifying verbal MWEs in running texts. Verbal MWEs include idioms (let the cat out of the bag), light verb constructions (make a decision), verb-particle constructions (give up), and inherently reflexive verbs (se suicider 'to suicide' in French). VMWEs were annotated according to the universal guidelines in 18 languages. The corpora are provided in the parsemetsv format, inspired by the CONLL-U format. For most languages, paired files in the CONLL-U format - not necessarily using UD tagsets - containing parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training and test data, tools and the universal guidelines file.
Rights:: PARSEME Shared Task Data (v. 1.0) Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.0, and PUB

27. Annotated corpora and tools of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions (edition 1.1)

Creator:: Ramisch, Carlos, Cordeiro, Silvio Ricardo, Savary, Agata, Vincze, Veronika, Barbu Mititelu, Verginica, Bhatia, Archna, Buljan, Maja, Candito, Marie, Gantar, Polona, Giouli, Voula, Güngör, Tunga, Hawwari, Abdelati, Iñurrieta, Uxoa, Kovalevskaitė, Jolanta, Krek, Simon, Lichte, Timm, Liebeskind, Chaya, Monti, Johanna, Parra Escartín, Carla, QasemiZadeh, Behrang, Ramisch, Renata, Schneider, Nathan, Stoyanova, Ivelina, Vaidya, Ashwini, Walsh, Abigail, Aceta, Cristina, Aduriz, Itziar, Antoine, Jean-Yves, Arhar Holdt, Špela, Berk, Gözde, Bielinskienė, Agnė, Blagus, Goranka, Boizou, Loic, Bonial, Claire, Caruso, Valeria, Čibej, Jaka, Constant, Matthieu, Cook, Paul, Diab, Mona, Dimitrova, Tsvetana, Ehren, Rafael, Elbadrashiny, Mohamed, Elyovich, Hevi, Erden, Berna, Estarrona, Ainara, Fotopoulou, Aggeliki, Foufi, Vassiliki, Geeraert, Kristina, van Gompel, Maarten, Gonzalez, Itziar, Gurrutxaga, Antton, Ha-Cohen Kerner, Yaakov, Ibrahim, Rehab, Ionescu, Mihaela, Jain, Kanishka, Jazbec, Ivo-Pavao, Kavčič, Teja, Klyueva, Natalia, Kocijan, Kristina, Kovács, Viktória, Kuzman, Taja, Leseva, Svetlozara, Ljubešić, Nikola, Malka, Ruth, Markantonatou, Stella, Martínez Alonso, Héctor, Matas, Ivana, McCrae, John, de Medeiros Caseli, Helena, Onofrei, Mihaela, Palka-Binkiewicz, Emilia, Papadelli, Stella, Parmentier, Yannick, Pascucci, Antonio, Pasquer, Caroline, Pia di Buono, Maria, Puri, Vandana, Raffone, Annalisa, Ratori, Shraddha, Riccio, Anna, Sangati, Federico, Shukla, Vishakha, Simkó, Katalin, Šnajder, Jan, Somers, Clarissa, Srivastava, Shubham, Stefanova, Valentina, Taslimipoor, Shiva, Theoxari, Natasa, Todorova, Maria, Urizar, Ruben, Villavicencio, Aline, and Zilio, Leonardo
Publisher:: PARSEME
Type:: text and corpus
Subject:: Multiword expressions, verbal multiword expressions, light-verb constructions, verb-particle constructions, inherently reflexive verbs, verbal idioms, and multi-verb constructions
Language:: Bulgarian, German, Modern Greek (1453-), Spanish, Persian, French, Hebrew, Hungarian, Italian, Lithuanian, Polish, Portuguese, Romanian, Slovenian, Turkish, Hindi, Basque, English, and Croatian
Description:: This multilingual resource contains corpora in which verbal MWEs have been manually annotated. VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). VMWEs were annotated according to the universal guidelines in 19 languages. The corpora are provided in the cupt format, inspired by the CONLL-U format. The corpora were used in the 1.1 edition of the PARSEME Shared Task (2018). For most languages, morphological and syntactic information – not necessarily using UD tagsets – including parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training, development and test data, as well as the evaluation tools used in the PARSEME Shared Task 1.1 (2018). The annotation guidelines are available online: http://parsemefr.lif.univ-mrs.fr/parseme-st-guidelines/1.1
Rights:: PARSEME Shared Task Data (v. 1.1) Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.1, and PUB

28. Annotated corpora and tools of the PARSEME Shared Task on Semi-Supervised Identification of Verbal Multiword Expressions (edition 1.2)

Creator:: Ramisch, Carlos, Guillaume, Bruno, Savary, Agata, Waszczuk, Jakub, Candito, Marie, Vaidya, Ashwini, Barbu Mititelu, Verginica, Bhatia, Archna, Iñurrieta, Uxoa, Giouli, Voula, Güngör, Tunga, Jiang, Menghan, Lichte, Timm, Liebeskind, Chaya, Monti, Johanna, Ramisch, Renata, Stymme, Sara, Walsh, Abigail, Xu, Hongzhi, Palka-Binkiewicz, Emilia, Ehren, Rafael, Stymne, Sara, Constant, Matthieu, Pasquer, Caroline, Parmentier, Yannick, Antoine, Jean-Yves, Carlino, Carola, Caruso, Valeria, Di Buono, Maria Pia, Pascucci, Antonio, Raffone, Annalisa, Riccio, Anna, Sangati, Federico, Speranza, Giulia, Cordeiro, Silvio Ricardo, de Medeiros Caseli, Helena, Miranda, Isaac, Rademaker, Alexandre, Vale, Oto, Villavicencio, Aline, Wick Pedro, Gabriela, Wilkens, Rodrigo, Zilio, Leonardo, Rizea, Monica-Mihaela, Ionescu, Mihaela, Onofrei, Mihaela, Chen, Jia, Ge, Xiaomin, Hu, Fangyuan, Hu, Sha, Li, Minli, Liu, Siyuan, Qin, Zhenzhen, Sun, Ruilong, Wang, Chenweng, Xiao, Huangyang, Yan, Peiyi, Yih, Tsy, Yu, Ke, Yu, Songping, Zeng, Si, Zhang, Yongchen, Zhao, Yun, Foufi, Vassiliki, Fotopoulou, Aggeliki, Markantonatou, Stella, Papadelli, Stella, Louizou, Sevasti, Aduriz, Itziar, Estarrona, Ainara, Gonzalez, Itziar, Gurrutxaga, Antton, Uria, Larraitz, Urizar, Ruben, Foster, Jennifer, Lynn, Teresa, Elyovitch, Hevi, Ha-Cohen Kerner, Yaakov, Malka, Ruth, Jain, Kanishka, Puri, Vandana, Ratori, Shraddha, Shukla, Vishakha, Srivastava, Shubham, Berk, Gozde, Erden, Berna, and Yirmibeşoğlu, Zeynep
Publisher:: PARSEME
Type:: text and corpus
Subject:: multiword expressions, verbal multiword expressions, light verb construction, verb-particle constructions, inherently reflexive verbs, verbal idioms, and multi-verb constructions
Language:: German, Modern Greek (1453-), Basque, French, Irish, Hebrew, Hindi, Italian, Polish, Portuguese, Romanian, Swedish, Turkish, and Chinese
Description:: This multilingual resource contains corpora in which verbal MWEs have been manually annotated, gathered at the occasion of the 1.2 edition of the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). VMWEs include idioms (let the cat out of the bag), light-verb constructions (make a decision), verb-particle constructions (give up), inherently reflexive verbs (help oneself), and multi-verb constructions (make do). For the 1.2 shared task edition, the data covers 14 languages, for which VMWEs were annotated according to the universal guidelines. The corpora are provided in the cupt format, inspired by the CONLL-U format. Morphological and syntactic information – not necessarily using UD tagsets – including parts of speech, lemmas, morphological features and/or syntactic dependencies are also provided. Depending on the language, the information comes from treebanks (e.g., Universal Dependencies) or from automatic parsers trained on treebanks (e.g., UDPipe). This item contains training, development and test data, as well as the evaluation tools used in the PARSEME Shared Task 1.2 (2020). The annotation guidelines are available online: http://parsemefr.lif.univ-mrs.fr/parseme-st-guidelines/1.2
Rights:: PARSEME Shared Task Data (v. 1.2) Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.2, and PUB

29. Annotated Corpus of Czech Case Law for Segmentation Tasks

Creator:: Harašta, Jakub, Šavelka, Jaromír, Kasl, František, and Míšek, Jakub
Publisher:: Masaryk University, Brno
Type:: text and corpus
Subject:: document segmentation and legal texts
Language:: Czech
Description:: Annotated corpus of 350 decision of Czech top-tier courts (Supreme Court, Supreme Administrative Court, Constitutional Court). 280 decisions were annotated by one trained annotator and then manually adjudicated by one trained curator. 70 decisions were annotated by two trained annotators and then manually adjudicated by one trained curator. Adjudication was conducted destructively, therefore dataset contains only the correct annotations and does not contain all original annotations. Corpus was developed as training and testing material for text segmentation tasks. Dataset contains decision segmented into Header, Procedural History, Submission/Rejoinder, Court Argumentation, Footer, Footnotes, and Dissenting Opinion. Segmentation allows to treat different parts of text differently even if it contains similar linguistic or other features.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

30. APE Shared Task WMT17: Human Post-edits Test Data DE-EN

Creator:: Turchi, Marco, Chatterjee, Rajen, and Negri, Matteo
Publisher:: Fondazione Bruno Kessler, Trento, Italy
Type:: text and corpus
Subject:: Human post-edits, machine translation, shared task, automatic post-editing, and post-editing
Language:: English
Description:: Human post-edited test sentences for the WMT 2017 Automatic post-editing task. This consists in 2,000 English sentences belonging to the IT domain and already tokenized. Source and target segments can be downloaded from: https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2132. All data is provided by the EU project QT21 (http://www.qt21.eu/).
Rights:: AGREEMENT ON THE USE OF DATA IN QT21 APE Task, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-TAUS_QT21, and PUB

31. APE Shared Task WMT17: Human Post-edits Test Data EN-DE

Creator:: Turchi, Marco, Chatterjee, Rajen, and Negri, Matteo
Publisher:: Fondazione Bruno Kessler, Trento, Italy
Type:: text and corpus
Subject:: machine translation, human post-edits, shared task, automatic post-editing, and post-editing
Language:: German
Description:: Human post-edited test sentences for the WMT 2017 Automatic post-editing task. This consists in 2,000 German sentences belonging to the IT domain and already tokenized. Source and target segments can be downloaded from: https://lindat.mff.cuni.cz/repository/xmlui/handle/11372/LRT-2133. All data is provided by the EU project QT21 (http://www.qt21.eu/).
Rights:: AGREEMENT ON THE USE OF DATA IN QT21 APE Task, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-TAUS_QT21, and PUB

32. APE Shared Task WMT18: Human Post-edits and References Test Data EN-DE PBSMT

Creator:: Turchi, Marco, Negri, Matteo, and Chatterjee, Rajen
Publisher:: Fondazione Bruno Kessler, Trento, Italy
Type:: text and corpus
Subject:: automatic post-editing, post-editing, phrase-based MT, and reference translation
Language:: German
Description:: Human post-edited and reference test sentences for the En-De PBSMT WMT 2018 Automatic post-editing task. This consists of 2,000 German sentences for each file belonging to the IT domain and already tokenized. All data is provided by the EU project QT21 (http://www.qt21.eu/).
Rights:: AGREEMENT ON THE USE OF DATA IN QT21 APE Task, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-TAUS_QT21, and PUB

33. Arabic Phonetic Rules

Creator:: Mustafa, Ebtihal and Bouzoubaa, Karim
Publisher:: languages journal
Type:: text, other, and lexicalConceptualResource
Subject:: Arabic and phonetic rules
Language:: Arabic
Description:: Description: this xml file describes the Arabic phonetic constraints (rules) resulting from the analysis of the lexicons(Taj Alarous, Al ain, Lisan Al arab, Alwassit and almoassir ). These rules are to be applied to Arabic roots and are classified into a number of categories. Each category has a certain type of constraints as follow: The first category defines that the root must not consist of three identical letters. The second category defines that the root must not start with two repeating letters. The third category lists the letters that must not occur in the same root, regardless of their order. The fourth category lists the letters that may not be used together in a certain order in a root. ISLRN: 190-535-098-473-3
Rights:: Creative Commons - Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), http://creativecommons.org/licenses/by-nc/4.0/, and PUB

34. Arabic Triliteral roots Lexicon

Creator:: Mustafa, Ebtihal and Bouzoubaa, Karim
Publisher:: MDPI language jurnal
Type:: text, lexicon, and lexicalConceptualResource
Subject:: Arabic language, Arabic roots, lexicons, phonetic system, bigram frequencies, and roots weight.
Language:: Arabic
Description:: Description: This xml file is a lexicon containing all 21952 (28x28x28) Arabic triliteral combinations (roots). the file is split into three parts as follow: the first part contains the phonetic constraints that must be taken into account in the formation of Arabic roots (for more details see all_phonetic_rules.xml in http://arabic.emi.ac.ma/alelm/?q=Resources). the second part contains the lexicons that were used to create this lexicon (see in lexicons tag). the third part contains the roots. ISLRN: 813-907-570-946-2
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

35. Arabic WordNet ontology

Creator:: Abouenour, Lahcen, Bouzoubaa, Karim, and Rosso, Paulo
Publisher:: Wordnet
Type:: text, wordnet, and lexicalConceptualResource
Subject:: WordNet
Language:: Arabic
Description:: This improved version is an extension of the original Arabic Wordnet (http://globalwordnet.org/arabic-wordnet/awn-browser/), it was enriched by new verbs, nouns including the broken plurals that is a specific form for Arabic words.
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. Artificial Treebank with Ellipsis

Creator:: Droganova, Kira, Zeman, Daniel, Kanerva, Jenna, and Ginter, Filip
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: universal dependencies, ellipsis, and gapping
Language:: English, Czech, Finnish, Russian, and Slovak
Description:: Artificially created treebank of elliptical constructions (gapping), in the annotation style of Universal Dependencies. Data taken from UD 2.1 release, and from large web corpora parsed by two parsers. Input data are filtered, sentences are identified where gapping could be applied, then those sentences are transformed, one or more words are omitted, resulting in a sentence with gapping. Details in Droganova et al.: Parse Me if You Can: Artificial Treebanks for Parsing Experiments on Elliptical Constructions, LREC 2018, Miyazaki, Japan.
Rights:: Licence Universal Dependencies v2.1, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.1, and PUB

37. Aspect-Term Annotated Customer Reviews in Czech

Creator:: Fiala, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: sentiment analysis, opinion target, and customer review
Language:: Czech
Description:: This dataset contains a number of user product reviews which are publicly available on the website of an established Czech online shop with electronic devices. Each review consists of negative and positive aspects of the product. This setting pushes the customer to rate important characteristics. We have selected 2000 positive and negative segments from these reviews and manually tagged their targets. Additionally, we selected 200 of the longest reviews and annotated them in the same way. The targets were either aspects of the evaluated product or some general attributes (e.g. price, ease of use).
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

38. ATCC: Pronunciation lexicon and n-gram counts for ASR module

Creator:: Šmídl, Luboš
Publisher:: University of West Bohemia, Department of Cybernetics
Type:: text, lexicalConceptualResource, and other
Subject:: pronunciation lexicon, n-gram counts, and language model
Language:: English
Description:: The corpus contains pronunciation lexicon and n-gram counts (unigrams, bigrams and trigrams) that can be used for constructing the language model for air traffic control communication domain. It could be used together with the Air Traffic Control Communication corpus (http://hdl.handle.net/11858/00-097C-0000-0001-CCA1-0). and Technology Agency of the Czech Republic, project No. TA01030476
Rights:: Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0), http://creativecommons.org/licenses/by-nc/3.0/, and PUB

39. AudioPSP 24.01: Audio recordings of proceedings of the Chamber of Deputies of the Parliament of the Czech Republic

Creator:: Kopp, Matyáš
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
Language:: Czech
Description:: This record contains audio recordings of proceedings of the Chamber of Deputies of the Parliament of the Czech Republic. The recordings have been provided by the official websites of the Chamber of Deputies, and the set contains them in their original format with no further processing. Recordings cover all available audio files from 2013-11-25 to 2023-07-26. Audio files are packed by year (2013-2023) and quarter (Q1-Q4) in tar archives audioPSP-YYYY-QN.tar. Furthermore, there are two TSV files: audioPSP-meta.quarterArchive.tsv contains metadata about archives, and audioPSP-meta.audioFile.tsv contains metadata about individual audio files.
Rights:: Public Domain Dedication (CC Zero), http://creativecommons.org/publicdomain/zero/1.0/, and PUB

40. Automatic Paraphrases of Czech Reference Sentences for WMT11, 13 and 14

Creator:: Barančíková, Petra and Tamchyna, Aleš
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: machine translation, automatic evaluation, and paraphrasing
Language:: Czech
Description:: This dataset contains automatic paraphrases of Czech official reference translations for the Workshop on Statistical Machine Translation shared task. The data covers the years 2011, 2013 and 2014. For each sentence, at most 10000 paraphrases were included (randomly selected from the full set). The goal of using this dataset is to improve automatic evaluation of machine translation outputs. If you use this work, please cite the following paper: Tamchyna Aleš, Barančíková Petra: Automatic and Manual Paraphrases for MT Evaluation. In proceedings of LREC, 2016.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB

41. Automatically generated spelling correction corpus for Czech (Czech-SEC-AG)

Creator:: Hajič, Jan, Náplava, Jakub, and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: spelling correction and natural language correction
Language:: Czech
Description:: Automatically generated spelling correction corpus for Czech (Czesl-SEC-AG) is a corpus containg text with automatically generated spelling errors. To create spelling errors, a character error model containing probabilities of character substitution, insertion, deletion and probabilities of swaping two adjacent characters is used. Besides these probabilities, also the probabilities of changing character casing are considered. The original clean text on which the spelling errors were generated is PDT3.0 (http://hdl.handle.net/11858/00-097C-0000-0023-1AAF-3). The original train/dev/test sentence split of PDT3.0 corpus is preserved in this dataset. Besides the data with artificial spelling errors, we also publish texts from which the character error model was created. These are the original manual transcript of an audiobook Švejk and its corrected version performed by authors of Korektor (http://ufal.mff.cuni.cz/korektor). These data are similarly to CzeSL Grammatical Error Correction Dataset (CzeSL-GEC: http://hdl.handle.net/11234/1-2143) processed into four sets based on error difficulty present.
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

42. Balaxan Corpus of Kurmanji

Creator:: Rahimi, Adel
Publisher:: Imam Khomeini International University
Type:: audio and corpus
Subject:: speech corpus and corpus
Language:: Northern Kurdish
Description:: Balaxan is the first speech corpus of Kurmanji Kurdish with 58 utterances by speakers of Kurmanji. utterances are divided into 4 categories based on their sentence structures: Declarative, Imperative, Interrogative, and Exclamatory. The corpus has subtitles both in Kurmanji (Latin alphabet) and English.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

43. 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

44. Broken plural list

Creator:: Ouamer, meriem, Bouzoubaa, Karim, and Tajmout, rachida
Publisher:: ALELM research group
Type:: text, wordList, and lexicalConceptualResource
Subject:: Broken plural
Language:: Arabic
Description:: An LMF conformant XML-based file containing a comprehensive Arabic broken plural list. The file contains 12,249 singular words with their corresponding BPs
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. BushBank

Creator:: Grác, Marek
Publisher:: Masaryk University, NLP Centre
Type:: text and corpus
Subject:: interannotator agreement, corpus, chunks, phrases, and clauses
Language:: Czech
Description:: Czech corpus annotated for NP and clause chunks by 3-11 annotators (with average inter-annotator agreement at 88%). It consists of 10,000 sentences.
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

53. CALEM (Comprehensive Arabic LEMmas)

Creator:: Namly, Driss, Bouzoubaa, Karim, and El Jihad, Abdelhamid
Publisher:: ALELM
Type:: text, lexicon, and lexicalConceptualResource
Subject:: lexicon, lemmatization, and stemming;
Language:: Arabic
Description:: Comprehensive Arabic LEMmas is a lexicon covering a large list of Arabic lemmas and their corresponding inflected word forms (stems) with details (POS + Root). Each lexical entry represents a lemma followed by all its possible stems and each stem is enriched by its morphological features especially the root and the POS. It is composed of 164,845 lemmas representing 7,200,918 stems, detailed as follow: 757 Arabic particles 2,464,631 verbal stems 4,735,587 nominal stems The lexicon is provided as an LMF conformant XML-based file in UTF8 encoding, which represents about 1,22 Gb of data. Citation: – Namly Driss, Karim Bouzoubaa, Abdelhamid El Jihad, and Si Lhoussain Aouragh. “Improving Arabic Lemmatization Through a Lemmas Database and a Machine-Learning Technique.” In Recent Advances in NLP: The Case of Arabic Language, pp. 81-100. Springer, Cham, 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

54. CEHugeWebCorpus

Creator:: Rüdiger, Jan Oliver
Publisher:: Rüdiger, Jan Oliver
Type:: text and corpus
Subject:: corpus, German, Germanistik, Web corpus, web corpora, and CorpusExplorer
Language:: German
Description:: This corpus was originally created for performance testing (server infrastructure CorpusExplorer - see: diskurslinguistik.net / diskursmonitor.de). It includes the filtered database (German texts only) of CommonCrawl (as of March 2018). First, the URLs were filtered according to their top-level domain (de, at, ch). Then the texts were classified using NTextCat and only uniquely German texts were included in the corpus. The texts were then annotated using TreeTagger (token, lemma, part-of-speech). 2.58 million documents - 232.87 million sentences - 3.021 billion tokens. You can use CorpusExplorer (http://hdl.handle.net/11234/1-2634) to convert this data into various other corpus formats (XML, JSON, Weblicht, TXM and many more).
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/

55. Česílko

Creator:: Hajič, Jan, Kuboň, Vladislav, and Homola, Petr
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: toolService
Subject:: machine translation and Czech-Slovak translation
Language:: Czech
Description:: Česílko is a tool enabling the fast and efficient translation from one source language into many target languages, which are mutually related.
Rights:: Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0), http://creativecommons.org/licenses/by-nc-nd/3.0/, and PUB

56. CLEF-TREC Q/A

Creator:: Abouenour, lahcen, Bouzoubaa, Karim, and Rosso, paolo
Publisher:: ALELM
Type:: text, other, and lexicalConceptualResource
Subject:: CLEF and TREC
Language:: Arabic
Description:: List of 2264 questions + answers of CLEF and TREC, translated to Arabic
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. 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

58. 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

59. 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

60. CoNLL 2009 Shared Task - Czech Data

Creator:: Hajič, Jan, Straňák, Pavel, and Štěpánek, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: conll-st and treebank
Language:: Czech
Description:: Czech data - both train and test+eval sets, as well as the valency dictionary - for the CoNLL 2009 Shared Task. Documentation is included. The data are generated from PDT 2.0. LDC catalog number: LDC2009E34B and MSM 0021620838 (http://ufal.mff.cuni.cz:8080/bib/?section=grant&id=116488695895567&mode=view)
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

61. CoNLL 2009 Shared Task Czech Trial Set

Creator:: Hajič, Jan, Straňák, Pavel, and Štěpánek, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: conll-st
Language:: Czech
Description:: Czech trial (example) data for CoNLL 2009 Shared Task. The data are generated from PDT 2.0. LDC2009E32B and MSM 0021620838 (http://ufal.mff.cuni.cz:8080/bib/?section=grant&id=116488695895567&mode=view)
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

62. CoNLL 2017 and 2018 Shared Task Blind and Preprocessed Test Data

Creator:: Zeman, Daniel and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: tokenization, word segmentation, morphology, tagging, syntax, parsing, and universal dependencies
Language:: Afrikaans, Arabic, Breton, Bulgarian, Russia Buriat, Catalan, Czech, Church Slavic, Danish, German, Modern Greek (1453-), English, Estonian, Basque, Faroese, Persian, Finnish, French, Old French (842-ca. 1400), Irish, Galician, Gothic, Ancient Greek (to 1453), Hebrew, Hindi, Croatian, Upper Sorbian, Hungarian, Armenian, Indonesian, Italian, Japanese, Kazakh, Northern Kurdish, Korean, Latin, Latvian, Dutch, Norwegian, Nigerian Pidgin, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Northern Sami, Spanish, Serbian, Swedish, Thai, Turkish, Uighur, Ukrainian, Urdu, Vietnamese, and Chinese
Description:: CoNLL 2017 and 2018 shared tasks: Multilingual Parsing from Raw Text to Universal Dependencies This package contains the test data in the form in which they ware presented to the participating systems: raw text files and files preprocessed by UDPipe. The metadata.json files contain lists of files to process and to output; README files in the respective folders describe the syntax of metadata.json. For full training, development and gold standard test data, see Universal Dependencies 2.0 (CoNLL 2017) Universal Dependencies 2.2 (CoNLL 2018) See the download links at http://universaldependencies.org/. For more information on the shared tasks, see http://universaldependencies.org/conll17/ http://universaldependencies.org/conll18/ Contents: conll17-ud-test-2017-05-09 ... CoNLL 2017 test data conll18-ud-test-2018-05-06 ... CoNLL 2018 test data conll18-ud-test-2018-05-06-for-conll17 ... CoNLL 2018 test data with metadata and filenames modified so that it is digestible by the 2017 systems.
Rights:: Licence Universal Dependencies v2.2, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.2, and PUB

63. CoNLL 2017 Shared Task - Automatically Annotated Raw Texts and Word Embeddings

Creator:: Ginter, Filip, Hajič, Jan, Luotolahti, Juhani, Straka, Milan, and Zeman, Daniel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, mlmodel, and languageDescription
Subject:: CoNLL 2017, word embeddings, and automatic annotation
Language:: Multiple languages
Description:: Automatic segmentation, tokenization and morphological and syntactic annotations of raw texts in 45 languages, generated by UDPipe (http://ufal.mff.cuni.cz/udpipe), together with word embeddings of dimension 100 computed from lowercased texts by word2vec (https://code.google.com/archive/p/word2vec/). For each language, automatic annotations in CoNLL-U format are provided in a separate archive. The word embeddings for all languages are distributed in one archive. Note that the CC BY-SA-NC 4.0 license applies to the automatically generated annotations and word embeddings, not to the underlying data, which may have different license and impose additional restrictions. Update 2018-09-03 =============== Added data in the 4 “surprise languages” from the 2017 ST: Buryat, Kurmanji, North Sami and Upper Sorbian. This has been promised before, during CoNLL-ST 2018 we gave the participants a link to this record saying the data was here. It wasn't, sorry. But now it is.
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

64. CoNLL 2017 Shared Task - UDPipe Baseline Models and Supplementary Materials

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, mlmodel, and languageDescription
Subject:: CoNLL 2017, tokenizer, POS tagger, lemmatization, tagger, parser, dependency parser, morphology, and treebank
Language:: Multiple languages
Description:: Baseline UDPipe models for CoNLL 2017 Shared Task in UD Parsing, and supplementary material. The models require UDPipe version at least 1.1 and are evaluated using the official evaluation script. The models are trained on a slightly different split of the official UD 2.0 CoNLL 2017 training data, so called baselinemodel split, in order to allow comparison of models even during the shared task. This baselinemodel split of UD 2.0 CoNLL 2017 training data is available for download. Furthermore, we also provide UD 2.0 CoNLL 2017 training data with automatically predicted morphology. We utilize the baseline models on development data and perform 10-fold jack-knifing (each fold is predicted with a model trained on the rest of the folds) on the training data. Finally, we supply all required data and hyperparameter values needed to replicate the baseline models.
Rights:: Licence Universal Dependencies v2.0, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.0, and PUB

65. CoNLL 2017 Shared Task System Outputs

Creator:: Zeman, Daniel, Potthast, Martin, Straka, Milan, Popel, Martin, Dozat, Timothy, Qi, Peng, Manning, Christopher, Shi, Tianze, Wu, Felix G., Chen, Xilun, Cheng, Yao, Björkelund, Anders, Falenska, Agnieszka, Yu, Xiang, Kuhn, Jonas, Che, Wanxiang, Guo, Jiang, Wang, Yuxuan, Zheng, Bo, Zhao, Huaipeng, Liu, Yang, Teng, Dechuan, Liu, Ting, Lim, Kyungtae, Poibeau, Thierry, Sato, Motoki, Manabe, Hitoshi, Noji, Hiroshi, Matsumoto, Yuji, Kırnap, Ömer, Önder, Berkay Furkan, Yuret, Deniz, Straková, Jana, Vania, Clara, Zhang, Xingxing, Lopez, Adam, Heinecke, Johannes, Asadullah, Munshi, Kanerva, Jenna, Luotolahti, Juhani, Ginter, Filip, Kuan, Yu, Sofroniev, Pavel, Schill, Erik, Hinrichs, Erhard, Nguyen, Dat Quoc, Dras, Mark, Johnson, Mark, Qian, Xian, Vilares, David, Gómez-Rodríguez, Carlos, Aufrant, Lauriane, Wisniewski, Guillaume, Yvon, François, Dumitrescu, Stefan Daniel, Boroş, Tiberiu, Tufiş, Dan, Das, Ayan, Zaffar, Affan, Sarkar, Sudeshna, Wang, Hao, Zhao, Hai, Zhang, Zhisong, Hornby, Ryan, Taylor, Clark, Park, Jungyeul, de Lhoneux, Miryam, Shao, Yan, Basirat, Ali, Kiperwasser, Eliyahu, Stymne, Sara, Goldberg, Yoav, Nivre, Joakim, Akkuş, Burak Kerim, Azizoglu, Heval, Cakici, Ruket, Moor, Christophe, Merlo, Paola, Henderson, James, Wang, Haozhou, Ji, Tao, Wu, Yuanbin, Lan, Man, de la Clergerie, Eric, Sagot, Benoît, Seddah, Djamé, More, Amir, Tsarfaty, Reut, Kanayama, Hiroshi, Muraoka, Masayasu, Yoshikawa, Katsumasa, Garcia, Marcos, and Gamallo, Pablo
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: dependency parser and parsebank
Language:: Arabic, Bulgarian, Russia Buriat, Czech, Catalan, Church Slavic, Danish, German, Modern Greek (1453-), English, Spanish, Estonian, Basque, Persian, Finnish, French, Irish, Galician, Gothic, Ancient Greek (to 1453), Hebrew, Hindi, Croatian, Upper Sorbian, Hungarian, Indonesian, Italian, Japanese, Kazakh, Northern Kurdish, Korean, Latin, Latvian, Dutch, Norwegian, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Northern Sami, Swedish, Turkish, Uighur, Ukrainian, Urdu, Vietnamese, and Chinese
Description:: This package contains the system outputs from the CoNLL 2017 Shared Task in Multilingual Parsing from Raw Text to Universal Dependencies.
Rights:: Licence Universal Dependencies v2.0, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.0, and PUB

66. CoNLL 2018 Shared Task - UDPipe Baseline Models and Supplementary Materials

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text, mlmodel, and languageDescription
Subject:: CoNLL 2018, tokenizer, POS tagger, lemmatization, tagger, parser, dependency parser, morphology, and treebank
Language:: Multiple languages
Description:: Baseline UDPipe models for CoNLL 2018 Shared Task in UD Parsing, and supplementary material. The models require UDPipe version at least 1.2 and are evaluated using the official evaluation script. The models were trained using a custom data split for treebanks where no development data is provided. Also, we trained an additional "Mixed" model, which uses 200 sentences from every training data. All information needed to replicate the model training (hyperparameters, modified train-dev split, and pre-computed word embeddings for the parser) are included in the archive. Additionaly, we provide UD 2.2 CoNLL 2018 training data with automatically predicted morphology. We utilize the baseline models on development data and perform 10-fold jack-knifing (each fold is predicted with a model trained on the rest of the folds) on the training data.
Rights:: Licence Universal Dependencies v2.2, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.2, and PUB

67. CoNLL 2018 Shared Task System Outputs

Creator:: Zeman, Daniel, Potthast, Martin, Duthoo, Elie, Mesnard, Olivier, Rybak, Piotr, Wróblewska, Alina, Che, Wanxiang, Liu, Yijia, Wang, Yuxuan, Zheng, Bo, Liu, Ting, Li, Zuchao, He, Shexia, Zhang, Zhuosheng, Zhao, Hai, Wu, Yingting, Tong, Jia-Jun, Nguyen, Dat Quoc, Verspoor, Karin, Wan, Hui, Naseem, Tahira, Lee, Young-Suk, Castelli, Vittorio, Ballesteros, Miguel, Hershcovich, Daniel, Abend, Omri, Rappoport, Ari, Smith, Aaron, Bohnet, Bernd, de Lhoneux, Miryam, Nivre, Joakim, Shao, Yan, Stymne, Sara, Kırnap, Ömer, Dayanık, Erenay, Yuret, Deniz, Kanerva, Jenna, Ginter, Filip, Miekka, Niko, Leino, Akseli, Salakoski, Tapio, Lim, KyungTae, Park, Cheoneum, Lee, Changki, Poibeau, Thierry, Bhat, Riyaz Ahmad, Bhat, Irshad, Bangalore, Srinivas, Qi, Peng, Dozat, Timothy, Zhang, Yuhao, Manning, Christopher, Boroș, Tiberiu, Dumitrescu, Stefan Daniel, Burtica, Ruxandra, Arakelyan, Gor, Hambardzumyan, Karen, Khachatrian, Hrant, Rosa, Rudolf, Mareček, David, Straka, Milan, Seker, Amit, More, Amir, Tsarfaty, Reut, Önder, Berkay Furkan, Gümeli, Can, Jawahar, Ganesh, Muller, Benjamin, Fethi, Amal, Martin, Louis, Villemonte de la Clergerie, Eric, Sagot, Benoît, Seddah, Djamé, Özateş, Şaziye Betül, Özgür, Arzucan, Gungor, Tunga, Öztürk, Balkız, Ji, Tao, Liu, Yufang, Wang, Yijun, Wu, Yuanbin, Lan, Man, Chen, Danlu, Lin, Mengxiao, Hu, Zhifeng, and Qiu, Xipeng
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: parsed data, conllu, and universal dependencies
Language:: Afrikaans, Arabic, Breton, Bulgarian, Russia Buriat, Catalan, Czech, Church Slavic, Danish, German, Modern Greek (1453-), English, Estonian, Basque, Faroese, Persian, Finnish, French, Old French (842-ca. 1400), Irish, Galician, Gothic, Ancient Greek (to 1453), Hebrew, Hindi, Croatian, Upper Sorbian, Hungarian, Armenian, Indonesian, Italian, Japanese, Kazakh, Northern Kurdish, Korean, Latin, Latvian, Dutch, Norwegian, Nigerian Pidgin, Polish, Portuguese, Romanian, Russian, Slovak, Slovenian, Northern Sami, Spanish, Serbian, Swedish, Thai, Turkish, Uighur, Ukrainian, Urdu, Vietnamese, and Chinese
Description:: Test data parsed by systems submitted to the CoNLL 2018 UD parsing shared task.
Rights:: Licence Universal Dependencies v2.2, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.2, and PUB

68. Continuous Rating; Supplementary materials

Creator:: Javorský, Dávid, Macháček, Dominik, and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: manual evaluation, simultaneous speech subtitling, Continuous Rating, and questionnaire evaluation
Language:: German and Czech
Description:: Collected data from Continuous Rating evaluation study; collected Continuous Rating scores and Questionnaires.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

69. 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

70. 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

71. 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

72. Coreference in Universal Dependencies 1.1 (CorefUD 1.1)

Creator:: Novák, Michal, Popel, Martin, Žabokrtský, Zdeněk, Zeman, Daniel, Nedoluzhko, Anna, Acar, Kutay, Bourgonje, Peter, Cinková, Silvie, 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, 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:: dependency, treebank, coreference, bridging relations, and harmonized annotation
Language:: Catalan, Czech, English, French, German, Hungarian, Lithuanian, Norwegian, 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 1.1 consists of 21 datasets for 13 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 17 datasets for 12 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 2 for Hungarian, 1 for Lithuanian, 2 for Norwegian, 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 1.0, the version 1.1 comprises new languages and corpora, namely Hungarian-KorKor, Norwegian-BokmaalNARC, Norwegian-NynorskNARC, and Turkish-ITCC. In addition, the English GUM dataset has been updated to a newer and larger version, and the conversion pipelines for most datasets have been refined (a list of all changes in each dataset can be found in the corresponding README file).
Rights:: Licence CorefUD v1.1, https://lindat.mff.cuni.cz/repository/xmlui/page/license-corefud-1.1, and PUB

73. 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

74. CORMAP - Corpus for Moroccan Arabic Processing

Creator:: tachicart, ridouane and bouzoubaa, karim
Publisher:: ALELM
Type:: text and corpus
Subject:: corpus
Language:: Arabic and Moroccan Arabic
Description:: This resource is a corpus containing 34k Moroccan Colloquial Arabic sentences collected from different sources. The sentences are written in Arabic letters. This resource can be useful in some NLP applications such as Language Identification.
Rights:: Licence Universal Dependencies v2.1, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-UD-2.1, and PUB

75. CorPipe 23 multilingual CorefUD 1.1 model (corpipe23-corefud1.1-231206)

Creator:: Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: tool and toolService
Subject:: coreference resolution, CorPipe, and CorefUD
Language:: Catalan, Czech, German, English, Spanish, French, Hungarian, Lithuanian, Norwegian Bokmål, Norwegian Nynorsk, Polish, Russian, and Turkish
Description:: The `corpipe23-corefud1.1-231206` is a `mT5-large`-based multilingual model for coreference resolution usable in CorPipe 23 (https://github.com/ufal/crac2023-corpipe). It is released under the CC BY-NC-SA 4.0 license. The model is language agnostic (no _corpus id_ on input), so it can be used to predict coreference in any `mT5` language (for zero-shot evaluation, see the paper). However, note that the empty nodes must be present already on input, they are not predicted (the same settings as in the CRAC23 shared task).
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

76. Corpus for training and evaluating diacritics restoration systems

Creator:: Náplava, Jakub, Straka, Milan, Hajič, Jan, and Straňák, Pavel
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: diacritical marks generation and natural language correction
Language:: Czech, Vietnamese, Romanian, Polish, Slovak, Spanish, Croatian, Irish, Latvian, Hungarian, French, and Turkish
Description:: Corpus of texts in 12 languages. For each language, we provide one training, one development and one testing set acquired from Wikipedia articles. Moreover, each language dataset contains (substantially larger) training set collected from (general) Web texts. All sets, except for Wikipedia and Web training sets that can contain similar sentences, are disjoint. Data are segmented into sentences which are further word tokenized. All data in the corpus contain diacritics. To strip diacritics from them, use Python script diacritization_stripping.py contained within attached stripping_diacritics.zip. This script has two modes. We generally recommend using method called uninames, which for some languages behaves better. The code for training recurrent neural-network based model for diacritics restoration is located at https://github.com/arahusky/diacritics_restoration.
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

77. Corpus of precisely articulated Czech speech

Creator:: Hanzlíček, Zdeněk, Kochová, Pavla, Tihelka, Daniel, Kövérová, Markéta, Matoušek, Jindřich, and Ševeček, Pavel
Publisher:: University of West Bohemia, Department of Cybernetics and Lingea, s.r.o.
Type:: audio and corpus
Subject:: speech corpus, text-to-speech (TTS), speech synthesis, and hyperarticulated speech
Language:: Czech
Description:: The corpus contains speech data of 2 Czech native speakers, male and female. The speech is very precisely articulated up to hyper-articulated, and the speech rate is low. The speech data with a highlighted articulation is suitable for teaching foreigners the Czech language, and it can also be used for people with hearing or speech impairment. The recorded sentences can be used either directly, e.g., as a part of educational material, or as source data for building complex educational systems incorporating speech synthesis technology. All recorded sentences were precisely orthographically annotated and phonetically segmented, i.e., split into phones, using modern neural network-based methods.
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. COSTRA 1.0: A Dataset of Complex Sentence Transformations

Creator:: Barančíková, Petra and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: sentences, sentence embeddings, paraphrases, and semantic relations
Language:: Czech
Description:: COSTRA 1.0 is a dataset of Czech complex sentence transformations. The dataset is intended for the study of sentence-level embeddings beyond simple word alternations or standard paraphrasing. The dataset consist of 4,262 unique sentences with average length of 10 words, illustrating 15 types of modifications such as simplification, generalization, or formal and informal language variation. The hope is that with this dataset, we should be able to test semantic properties of sentence embeddings and perhaps even to find some topologically interesting “skeleton” in the sentence embedding space.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

79. COSTRA 1.1: A Dataset of Complex Sentence Transformations and Comparisons

Creator:: Barančíková, Petra and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: paraphrases, sentence embeddings, evaluation, and sentence
Language:: Czech
Description:: Costra 1.1 is a new dataset for testing geometric properties of sentence embeddings spaces. In particular, it concentrates on examining how well sentence embeddings capture complex phenomena such paraphrases, tense or generalization. The dataset is a direct expansion of Costra 1.0, which was extended with more sentences and sentence comparisons.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

80. Covid-19 Thesaurus

Creator:: Fener, Patricia
Publisher:: Institute for scientific and technical information (Inist) - CNRS/UAR76
Type:: thesaurus, text, and lexicalConceptualResource
Subject:: COVID-19, SARS coronavirus, Middle-East coronavirus, SARS-CoV, and MERS-CoV
Language:: French and English
Description:: This bilingual thesaurus (French-English), developed at Inist-CNRS, covers the concepts from the emerging COVID-19 outbreak which reminds the past SARS coronavirus outbreak and Middle East coronavirus outbreak. This thesaurus is based on the vocabulary used in scientific publications for SARS-CoV-2 and other coronaviruses, like SARS-CoV and MERS-CoV. It provides a support to explore the coronavirus infectious diseases. The thesaurus can be browsed and queried by humans and machines on the Loterre portal (https://www.loterre.fr), via an API and an rdf triplestore. It is also downloadable in PDF, SKOS, csv and json-ld formats. The thesaurus is made available under a CC-by 4.0 license.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), PUB, and http://creativecommons.org/licenses/by/4.0/

81. CsEnVi Pairwise Parallel Corpora

Creator:: Hoang, Duc Tam and Bojar, Ondřej
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: corpus, Vietnamese, parallel corpus, Czech-Vietnamese corpus, and English-Vietnamese corpus
Language:: Czech, English, and Vietnamese
Description:: CsEnVi Pairwise Parallel Corpora consist of Vietnamese-Czech parallel corpus and Vietnamese-English parallel corpus. The corpora were assembled from the following sources: - OPUS, the open parallel corpus is a growing multilingual corpus of translated open source documents. The majority of Vi-En and Vi-Cs bitexts are subtitles from movies and television series. The nature of the bitexts are paraphrasing of each other's meaning, rather than translations. - TED talks, a collection of short talks on various topics, given primarily in English, transcribed and with transcripts translated to other languages. In our corpus, we use 1198 talks which had English and Vietnamese transcripts available and 784 talks which had Czech and Vietnamese transcripts available in January 2015. The size of the original corpora collected from OPUS and TED talks is as follows: CS/VI EN/VI Sentence 1337199/1337199 2035624/2035624 Word 9128897/12073975 16638364/17565580 Unique word 224416/68237 91905/78333 We improve the quality of the corpora in two steps: normalizing and filtering. In the normalizing step, the corpora are cleaned based on the general format of subtitles and transcripts. For instance, sequences of dots indicate explicit continuation of subtitles across multiple time frames. The sequences of dots are distributed differently in the source and the target side. Removing the sequence of dots, along with a number of other normalization rules, improves the quality of the alignment significantly. In the filtering step, we adapt the CzEng filtering tool [1] to filter out bad sentence pairs. The size of cleaned corpora as published is as follows: CS/VI EN/VI Sentence 1091058/1091058 1113177/1091058 Word 6718184/7646701 8518711/8140876 Unique word 195446/59737 69513/58286 The corpora are used as training data in [2]. References: [1] Ondřej Bojar, Zdeněk Žabokrtský, et al. 2012. The Joy of Parallelism with CzEng 1.0. Proceedings of LREC2012. ELRA. Istanbul, Turkey. [2] Duc Tam Hoang and Ondřej Bojar, The Prague Bulletin of Mathematical Linguistics. Volume 104, Issue 1, Pages 75–86, ISSN 1804-0462. 9/2015
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

82. 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

83. 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

84. 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

85. CWC2011

Creator:: Spoustová, Johanka and Spousta, Miroslav
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: corpus, Czech, and web
Language:: Czech
Description:: Web corpus of Czech, created in 2011. Contains newspapers+magazines, discussions, blogs. See http://www.lrec-conf.org/proceedings/lrec2012/summaries/120.html for details. and GA405/09/0278
Rights:: Creative Commons - Attribution 3.0 Unported (CC BY 3.0), http://creativecommons.org/licenses/by/3.0/, and PUB

86. Czech and English abstracts of ÚFAL papers

Creator:: Rosa, Rudolf
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 document-aligned parallel corpus of English and Czech abstracts of scientific papers published by authors from the Institute of Formal and Applied Linguistics, Charles University in Prague, as reported in the institute's system Biblio. For each publication, the authors are obliged to provide both the original abstract in Czech or English, and its translation into English or Czech, respectively. No filtering was performed, except for removing entries missing the Czech or English abstract, and replacing newline and tabulator characters by spaces.
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

87. 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

88. Czech and English Reflective Dataset (CEReD)

Creator:: Štefánik, Michal and Nehyba, Jan
Publisher:: Masaryk University, Brno
Type:: text and corpus
Subject:: reflective writing, reflective categories, pre-service teachers, and hand annotation
Language:: English and Czech
Description:: The database contains annotated reflective sentences, which fall into the categories of reflective writing according to Ullmann's (2019) model. The dataset is ready to replicate these categories' prediction using machine learning. Available from: https://anonymous.4open.science/repository/c856595c-dfc2-48d7-aa3d-0ccc2648c4dc/data
Rights:: Creative Commons - Attribution 4.0 International (CC BY 4.0), http://creativecommons.org/licenses/by/4.0/, and PUB

89. Czech Court Decisions Corpus (CzCDC 1.0)

Creator:: Novotná, Tereza and Harašta, Jakub
Publisher:: Faculty of Law, Masaryk University
Type:: text and corpus
Subject:: legal texts, judicial decisions, and court decisions
Language:: Czech
Description:: This is the Czech Court Decisions Corpus (CzCDC 1.0). This corpus contains whole texts of the decisions from three top-tier courts (Supreme, Supreme Administrative and Constitutional court) in Czech republic. Court decisions are published from 1st January 1993 to 30th September 2018. The language of decisions is Czech. Content of decisions is unedited and obtained directly from the competent court. Decisions are in .txt format in three folders divided by courts. Corpus contains three .csv files containing the list of all decisions with four columns: - name of the file: exact file name of a decision with extension .txt; - decision identifier (docket number): official identification of the decision as issued by the court; - date of decision: in ISO 8601 (YYYY-MM-DD); - court abbreviation: SupCo for Supreme Court, SupAdmCo for Supreme Administrative Court, ConCo for Constitutional Court Statistics: - SupCo: 111 977 decisions, 23 699 639 lines, 224 061 129 words, 1 462 948 200 bits; - SupAdmCo: 52 660 decisions, 18 069 993 lines, 137 839 985 words, 1 067 826 507 bits; - ConCo: 73 086 decisions, 6 178 371 lines, 98 623 753 words, 664 657 755 bits - all courts combined: 237 723 decisions, 47 948 003 lines, 460 524 867 words, 3 195 432 462 bits
Rights:: Creative Commons - Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), http://creativecommons.org/licenses/by-nc/4.0/, and PUB

90. Czech Grammar Agreement Dataset for Evaluation of Language Models

Creator:: Baisa, Vít
Publisher:: Masaryk University, NLP Centre
Type:: text and corpus
Subject:: agreement, past tense verb suffix, language model, and training data
Language:: Czech
Description:: AGREE is a dataset and task for evaluation of language models based on grammar agreement in Czech. The dataset consists of sentences with marked suffixes of past tense verbs. The task is to choose the right verb suffix which depends on gender, number and animacy of subject. It is challenging for language models because 1) Czech is morphologically rich, 2) it has relatively free word order, 3) high out-of-vocabulary (OOV) ratio, 4) predicate and subject can be far from each other, 5) subjects can be unexpressed and 6) various semantic rules may apply. The task provides a straightforward and easily reproducible way of evaluating language models on a morphologically rich language.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB

91. Czech HS Contracts Dataset (CHSC) 1.0

Creator:: Szabó, Adam and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: Czech, document classification, contracts, and Hlídač státu
Language:: Czech
Description:: Czech Contracts dataset was created as a part of the thesis Low-resource Text Classification (2021), A. Szabó, MFF UK. Contracts are obtained from the Hlídač Státu web portal. Labels in the development and training set are automatically classified on the basis of the keyword method according to the thesis Automatická klasifikace smluv pro portál HlidacSmluv.cz, J. Maroušek (2020), MFF UK. For this reason, the goal in the classification is not to achieve 100% on the development set, as the classification contains a certain amount of noise. The test set is manually annotated. The dataset contains a total of 97493 contracts.
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/

92. Czech image captioning, machine translation, and sentiment analysis (Neural Monkey models)

Creator:: Libovický, Jindřich, Rosa, Rudolf, Helcl, Jindřich, and Popel, Martin
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: suiteOfTools and toolService
Subject:: sentiment analysis, machine translation, image captioning, neural networks, transformer, and Neural Monkey
Language:: Czech and English
Description:: This submission contains trained end-to-end models for the Neural Monkey toolkit for Czech and English, solving three NLP tasks: machine translation, image captioning, and sentiment analysis. The models are trained on standard datasets and achieve state-of-the-art or near state-of-the-art performance in the tasks. The models are described in the accompanying paper. The same models can also be invoked via the online demo: https://ufal.mff.cuni.cz/grants/lsd There are several separate ZIP archives here, each containing one model solving one of the tasks for one language. To use a model, you first need to install Neural Monkey: https://github.com/ufal/neuralmonkey To ensure correct functioning of the model, please use the exact version of Neural Monkey specified by the commit hash stored in the 'git_commit' file in the model directory. Each model directory contains a 'run.ini' Neural Monkey configuration file, to be used to run the model. See the Neural Monkey documentation to learn how to do that (you may need to update some paths to correspond to your filesystem organization). The 'experiment.ini' file, which was used to train the model, is also included. Then there are files containing the model itself, files containing the input and output vocabularies, etc. For the sentiment analyzers, you should tokenize your input data using the Moses tokenizer: https://pypi.org/project/mosestokenizer/ For the machine translation, you do not need to tokenize the data, as this is done by the model. For image captioning, you need to: - download a trained ResNet: http://download.tensorflow.org/models/resnet_v2_50_2017_04_14.tar.gz - clone the git repository with TensorFlow models: https://github.com/tensorflow/models - preprocess the input images with the Neural Monkey 'scripts/imagenet_features.py' script (https://github.com/ufal/neuralmonkey/blob/master/scripts/imagenet_features.py) -- you need to specify the path to ResNet and to the TensorFlow models to this script Feel free to contact the authors of this submission in case you run into problems!
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

93. Czech image captioning, machine translation, sentiment analysis and summarization (Neural Monkey models)

Creator:: Libovický, Jindřich, Rosa, Rudolf, Helcl, Jindřich, and Popel, Martin
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: suiteOfTools and toolService
Subject:: sentiment analysis, machine translation, image captioning, neural networks, transformer, Neural Monkey, and summarization
Language:: Czech and English
Description:: This submission contains trained end-to-end models for the Neural Monkey toolkit for Czech and English, solving four NLP tasks: machine translation, image captioning, sentiment analysis, and summarization. The models are trained on standard datasets and achieve state-of-the-art or near state-of-the-art performance in the tasks. The models are described in the accompanying paper. The same models can also be invoked via the online demo: https://ufal.mff.cuni.cz/grants/lsd In addition to the models presented in the referenced paper (developed and published in 2018), we include models for automatic news summarization for Czech and English developed in 2019. The Czech models were trained using the SumeCzech dataset (https://www.aclweb.org/anthology/L18-1551.pdf), the English models were trained using the CNN-Daily Mail corpus (https://arxiv.org/pdf/1704.04368.pdf) using the standard recurrent sequence-to-sequence architecture. There are several separate ZIP archives here, each containing one model solving one of the tasks for one language. To use a model, you first need to install Neural Monkey: https://github.com/ufal/neuralmonkey To ensure correct functioning of the model, please use the exact version of Neural Monkey specified by the commit hash stored in the 'git_commit' file in the model directory. Each model directory contains a 'run.ini' Neural Monkey configuration file, to be used to run the model. See the Neural Monkey documentation to learn how to do that (you may need to update some paths to correspond to your filesystem organization). The 'experiment.ini' file, which was used to train the model, is also included. Then there are files containing the model itself, files containing the input and output vocabularies, etc. For the sentiment analyzers, you should tokenize your input data using the Moses tokenizer: https://pypi.org/project/mosestokenizer/ For the machine translation, you do not need to tokenize the data, as this is done by the model. For image captioning, you need to: - download a trained ResNet: http://download.tensorflow.org/models/resnet_v2_50_2017_04_14.tar.gz - clone the git repository with TensorFlow models: https://github.com/tensorflow/models - preprocess the input images with the Neural Monkey 'scripts/imagenet_features.py' script (https://github.com/ufal/neuralmonkey/blob/master/scripts/imagenet_features.py) -- you need to specify the path to ResNet and to the TensorFlow models to this script The summarization models require input that is tokenized with Moses Tokenizer (https://github.com/alvations/sacremoses) and lower-cased. Feel free to contact the authors of this submission in case you run into problems!
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

94. Czech Legal Text Treebank

Creator:: Kríž, Vincent, Hladká, Barbora, and Urešová, Zdeňka
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: treebank, corpus, Czech, legal texts, and legal domain
Language:: Czech
Description:: The Czech Legal Text Treebank (CLTT) is a collection of 1133 manually annotated dependency trees. CLTT consists of two legal documents: The Accounting Act (563/1991 Coll., as amended) and Decree on Double-entry Accounting for undertakers (500/2002 Coll., as amended).
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

95. Czech Legal Text Treebank 2.0

Creator:: Kríž, Vincent and Hladká, Barbora
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: treebank, Prague dependencies, named entities, and semantic relations
Language:: Czech
Description:: The Czech Legal Text Treebank 2.0 (CLTT 2.0) annotates the same texts as the CLTT 1.0. These texts come from the legal domain and they are manually syntactically annotated. The CLTT 2.0 annotation on the syntactic layer is more elaborate than in the CLTT 1.0 from various aspects. In addition, new annotation layers were added to the data: (i) the layer of accounting entities, and (ii) the layer of semantic entity relations.
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

96. Czech Malach Cross-lingual Speech Retrieval Test Collection

Creator:: Galuščáková, Petra, Pecina, Pavel, Hoffmannová, Petra, Hajič, Jan, Ircing, Pavel, and Švec, Jan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: audio and corpus
Subject:: annotated corpus, corpus, speech corpus, annotation, audio, and multilingual
Language:: Czech, English, French, German, and Spanish
Description:: The package contains Czech recordings of the Visual History Archive which consists of the interviews with the Holocaust survivors. The archive consists of audio recordings, four types of automatic transcripts, manual annotations of selected topics and interviews' metadata. The archive totally contains 353 recordings and 592 hours of interviews.
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

97. Czech Models (CNEC) for NameTag

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:: NameTag, Czech, and named entity recognition
Language:: Czech
Description:: Czech models for NameTag, providing recognition of named entities. The models are trained on Czech Named Entity Corpus 2.0 and 1.1. 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). Czech models are trained on Czech Named Entity Corpus, which was created by Magda Ševčíková, Zdeněk Žabokrtský, Jana Straková and Milan Straka. The recognizer research was supported by the projects MSM0021620838 and LC536 of Ministry of Education, Youth and Sports of the Czech Republic, 1ET101120503 of Academy of Sciences of the Czech Republic, LINDAT/CLARIN project of the Ministry of Education of the Czech Republic (project LM2010013), and partially by SVV project number 267 314. The research was performed by Jana Straková, Zdeněk Žabokrtský and Milan Straka. Czech models use MorphoDiTa as a tagger and lemmatizer, therefore MorphoDiTa Acknowledgements (http://ufal.mff.cuni.cz/morphodita#morphodita_acknowledgements) and Czech MorphoDiTa Model Acknowledgements (http://ufal.mff.cuni.cz/morphodita/users-manual#czech-morfflex-pdt_acknowledgements) apply.
Rights:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

98. Czech Models (MorfFlex CZ + PDT) for MorphoDiTa

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 and the PoS tagger is trained on PDT (Prague Dependency Treebank). 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:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

99. Czech Models (MorfFlex CZ 160310 + PDT 3.0) for MorphoDiTa 160310

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 160310 and the PoS tagger is trained on Prague Dependency Treebank 3.0 (PDT). 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:: Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0), http://creativecommons.org/licenses/by-nc-sa/3.0/, and PUB

100. Czech Models (MorfFlex CZ 161115 + PDT 3.0) for MorphoDiTa 161115

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 161115 and DeriNet 1.2 and the PoS tagger is trained on Prague Dependency Treebank 3.0 (PDT). 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

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