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8. 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

9. 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

10. DaMuEL 1.0: A Large Multilingual Dataset for Entity Linking

Creator:: Kubeša, David and Straka, Milan
Publisher:: Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:: text and corpus
Subject:: entity linking, NEL, NER, dataset, and knowledge base
Language:: Afrikaans, Arabic, Armenian, Basque, Belarusian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Korean, Latin, Latvian, Lithuanian, Maltese, Marathi, Modern Greek (1453-), Northern Sami, Norwegian Nynorsk, Persian, Polish, Portuguese, Romanian, Russian, Scottish Gaelic, Serbian, Slovak, Slovenian, Spanish, Swedish, Tamil, Telugu, Uighur, Ukrainian, Urdu, Vietnamese, and Wolof
Description:: We present DaMuEL, a large Multilingual Dataset for Entity Linking containing data in 53 languages. DaMuEL consists of two components: a knowledge base that contains language-agnostic information about entities, including their claims from Wikidata and named entity types (PER, ORG, LOC, EVENT, BRAND, WORK_OF_ART, MANUFACTURED); and Wikipedia texts with entity mentions linked to the knowledge base, along with language-specific text from Wikidata such as labels, aliases, and descriptions, stored separately for each language. The Wikidata QID is used as a persistent, language-agnostic identifier, enabling the combination of the knowledge base with language-specific texts and information for each entity. Wikipedia documents deliberately annotate only a single mention for every entity present; we further automatically detect all mentions of named entities linked from each document. The dataset contains 27.9M named entities in the knowledge base and 12.3G tokens from Wikipedia texts. The dataset is published under the CC BY-SA licence.
Rights:: Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB