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32. Morpho-syntactically annotated corpora provided for the PARSEME Shared Task on Semi-Supervised Identification of Verbal Multiword Expressions (edition 1.2)

Creator:
Guillaume, Bruno, Ramisch, Carlos, Waszczuk, Jakub, Monti, Johanna, Di Buono, Maria Pia, Sangati, Federico, Speranza, Giulia, Carlino, Carola, Güngör, Tunga, Yirmibeşoğlu, Zeynep, Sak, Haşim, Saraçlar, Murat, Giouli, Voula, Foufi, Vassiliki, Ramisch, Renata, Rademaker, Alexandre, Vale, Oto, Wilkens, Rodrigo, Candito, Marie, Crabbé, Benoît, Segonne, Vincent, Liebeskind, Chaya, Stymne, Sara, Hajič, Jan, Ginter, Filip, Luotolahti, Juhani, Straka, Milan, Zeman, Daniel, Barbu Mititelu, Verginica, Cristescu, Mihaela, Vaidya, Ashwini, Bhatia, Archna, Lichte, Timm, Ehren, Rafael, Jiang, Menghan, Xu, Hongzhi, Walsh, Abigail, Irimia, Elena, and Dowling, Meghan
Publisher:
PARSEME
Type:
text and corpus
Subject:
morphosyntactic annotation, dependency trees, and morphological analysis
Language:
German, Modern Greek (1453-), Basque, French, Irish, Hebrew, Hindi, Italian, Polish, Portuguese, Romanian, Swedish, Turkish, and Chinese
Description:
This multilingual resource contains corpora for 14 languages, gathered at the occasion of the 1.2 edition of the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). These corpora were meant to serve as additional "raw" corpora, to help discovering unseen verbal MWEs. The corpora are provided in CONLL-U (https://universaldependencies.org/format.html) format. They contain morphosyntactic annotations (parts of speech, lemmas, morphological features, and syntactic dependencies). Depending on the language, the information comes from treebanks (mostly Universal Dependencies v2.x) or from automatic parsers trained on UD v2.x treebanks (e.g., UDPipe). 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 Raw Corpus Data (v. 1.2) Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.2-raw, and PUB

33. Multilingual static embeddings for Verbal Multiword Expressions trained on PARSEME raw corpora

Creator:
Estève, Louis Clément, Savary, Agata, and Lavergne, Thomas
Publisher:
Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique
Type:
text, computationalLexicon, and lexicalConceptualResource
Subject:
verbal multiword expressions, word embeddings, and word2vec
Language:
German, Modern Greek (1453-), Basque, French, Irish, Hebrew, Hindi, Italian, Polish, Portuguese, Romanian, Swedish, Turkish, and Chinese
Description:
This resource is a set of 14 vector spaces for single words and Verbal Multiword Expressions (VMWEs) in different languages (German, Greek, Basque, French, Irish, Hebrew, Hindi, Italian, Polish, Brazilian Portuguese, Romanian, Swedish, Turkish, Chinese). They were trained with the Word2Vec algorithm, in its skip-gram version, on PARSEME raw corpora automatically annotated for morpho-syntax (http://hdl.handle.net/11234/1-3367). These corpora were annotated by Seen2Seen, a rule-based VMWE identifier, one of the leading tools of the PARSEME shared task version 1.2. VMWE tokens were merged into single tokens. The format of the vector space files is that of the original Word2Vec implementation by Mikolov et al. (2013), i.e. a binary format. For compression, bzip2 was used.
Rights:
PARSEME Shared Task Raw Corpus Data (v. 1.2) Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.2-raw, and PUB

34. OmegaWiki

Publisher:
Universität Bamberg, World Language Documentation Centre
Format:
application/octet-stream
Type:
lexicalConceptualResource
Language:
Afrikaans, Arabic, Basque, Bulgarian, Catalan, Chinese, Czech, Danish, Dutch, English, Esperanto, Estonian, Finnish, French, Galician, Georgian, Modern Greek (1453-), Hebrew, Hungarian, Icelandic, Indonesian, Interlingua (International Auxiliary Language Association), Irish, Italian, Japanese, Khmer, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Spanish, Swedish, Turkish, Ukrainian, and Welsh
Rights:
GFDL or CC and http://www.omegawiki.org/Licensing

35. PARSEME corpora annotated for verbal multiword expressions (version 1.3)

Creator:
Savary, Agata, Ramisch, Carlos, Guillaume, Bruno, Hawwari, Abdelati, Walsh, Abigail, Fotopoulou, Aggeliki, Bielinskienė, Agnė, Estarrona, Ainara, Gatt, Albert, Butler, Alexandra, Rademaker, Alexandre, Maldonado, Alfredo, Villavicencio, Aline, Farrugia, Alison, Muscat, Amanda, Gatt, Anabelle, Antić, Anđela, De Santis, Anna, Raffone, Annalisa, Riccio, Anna, Pascucci, Antonio, Gurrutxaga, Antton, Bhatia, Archna, Vaidya, Ashwini, Miral, Ayşenur, QasemiZadeh, Behrang, Priego Sanchez, Belem, Griciūtė, Bernadeta, Erden, Berna, Parra Escartín, Carla, Herrero, Carlos, Carlino, Carola, Pasquer, Caroline, Liebeskind, Chaya, Wang, Chenweng, Ben Khelil, Chérifa, Bonial, Claire, Somers, Clarissa, Aceta, Cristina, Krstev, Cvetana, Bejček, Eduard, Lindqvist, Ellinor, Erenmalm, Elsa, Palka-Binkiewicz, Emilia, Rimkute, Erika, Petterson, Eva, Cap, Fabienne, Hu, Fangyuan, Sangati, Federico, Wick Pedro, Gabriela, Speranza, Giulia, Jagfeld, Glorianna, Blagus, Goranka, Berk, Gözde, Attard, Greta, Eryiğit, Gülşen, Finnveden, Gustav, Martínez Alonso, Héctor, de Medeiros Caseli, Helena, Elyovich, Hevi, Xu, Hongzhi, Xiao, Huangyang, Miranda, Isaac, Jaknić, Isidora, El Maarouf, Ismail, Aduriz, Itziar, Gonzalez, Itziar, Matas, Ivana, Stoyanova, Ivelina, Jazbec, Ivo-Pavao, Busuttil, Jael, Waszczuk, Jakub, Findlay, Jamie, Bonnici, Janice, Šnajder, Jan, Antoine, Jean-Yves, Foster, Jennifer, Chen, Jia, Nivre, Joakim, Monti, Johanna, McCrae, John, Kovalevskaitė, Jolanta, Jain, Kanishka, Simkó, Katalin, Yu, Ke, Azzopardi, Kirsty, Adalı, Kübra, Uria, Larraitz, Zilio, Leonardo, Boizou, Loïc, van der Plas, Lonneke, Galea, Luke, Sarlak, Mahtab, Buljan, Maja, Cherchi, Manuela, Tanti, Marc, Di Buono, Maria Pia, Todorova, Maria, Candito, Marie, Constant, Matthieu, Shamsfard, Mehrnoush, Jiang, Menghan, Boz, Mert, Spagnol, Michael, Onofrei, Mihaela, Li, Minli, Elbadrashiny, Mohamed, Diab, Mona, Rizea, Monica-Mihaela, Hadj Mohamed, Najet, Theoxari, Natasa, Schneider, Nathan, Tabone, Nicole, Ljubešić, Nikola, Vale, Oto, Cook, Paul, Yan, Peiyi, Gantar, Polona, Ehren, Rafael, Fabri, Ray, Ibrahim, Rehab, Ramisch, Renata, Walles, Rinat, Wilkens, Rodrigo, Urizar, Ruben, Sun, Ruilong, Malka, Ruth, Galea, Sara Anne, Stymne, Sara, Louizou, Sevasti, Hu, Sha, Taslimipoor, Shiva, Ratori, Shraddha, Srivastava, Shubham, Cordeiro, Silvio Ricardo, Krek, Simon, Liu, Siyuan, Zeng, Si, Yu, Songping, Arhar Holdt, Špela, Markantonatou, Stella, Papadelli, Stella, Leseva, Svetlozara, Kuzman, Taja, Kavčič, Teja, Lynn, Teresa, Lichte, Timm, Pickard, Thomas, Dimitrova, Tsvetana, Yih, Tsy, Güngör, Tunga, Dinç, Tutkum, Iñurrieta, Uxoa, Tajalli, Vahide, Stefanova, Valentina, Caruso, Valeria, Puri, Vandana, Foufi, Vassiliki, Barbu Mititelu, Verginica, Vincze, Veronika, Kovács, Viktória, Shukla, Vishakha, Giouli, Voula, Ge, Xiaomin, Ha-Cohen Kerner, Yaakov, Öztürk, Yağmur, Yarandi, Yalda, Parmentier, Yannick, Zhang, Yongchen, Zhao, Yun, Urešová, Zdeňka, Yirmibeşoğlu, Zeynep, Qin, Zhenzhen, Stank, Cristescu, Mihaela, Zgreabăn, Bianca-Mădălina, Bărbulescu, Elena-Andreea, and Stanković, Ranka
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:
Arabic, Bulgarian, Czech, German, Modern Greek (1453-), English, Spanish, Basque, Persian, French, Irish, Hebrew, Hindi, Croatian, Hungarian, Lithuanian, Italian, Maltese, Polish, Portuguese, Romanian, Slovenian, Serbian, Swedish, Turkish, and Chinese
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). This is the first release of the corpora without an associated shared task. Previous version (1.2) was associated with the PARSEME Shared Task on semi-supervised Identification of Verbal MWEs (2020). The data covers 26 languages corresponding to the combination of the corpora for all previous three editions (1.0, 1.1 and 1.2) of the corpora. 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, ­­­­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). All corpora are split into training, development and test data, following the splitting strategy adopted for the PARSEME Shared Task 1.2. The annotation guidelines are available online: https://parsemefr.lis-lab.fr/parseme-st-guidelines/1.3 The .cupt format is detailed here: https://multiword.sourceforge.net/cupt-format/
Rights:
PARSEME Corpora v. 1.3 - Licence Agreement, https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.3, and PUB

36. Plaintext Wikipedia dump 2018

Creator:
Rosa, Rudolf
Publisher:
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:
text and corpus
Subject:
Wikipedia, text corpora, and monolingual corpus
Language:
Abkhazian, Achinese, Adyghe, Afrikaans, Akan, Tosk Albanian, Amharic, Old English (ca. 450-1100), Arabic, Official Aramaic (700-300 BCE), Aragonese, Egyptian Arabic, Assamese, Asturian, Atikamekw, Avaric, Aymara, South Azerbaijani, Azerbaijani, Bashkir, Bambara, Bavarian, Central Bikol, Belarusian, Bengali, Bislama, Banjar, Tibetan, Bosnian, Bishnupriya, Breton, Buginese, Bulgarian, Russia Buriat, Catalan, Min Dong Chinese, Cebuano, Czech, Chamorro, Chechen, Cherokee, Church Slavic, Chuvash, Cheyenne, Central Kurdish, Cornish, Corsican, Cree, Crimean Tatar, Kashubian, Welsh, Danish, German, Dinka, Dimli (individual language), Dhivehi, Lower Sorbian, Dzongkha, Modern Greek (1453-), English, Esperanto, Estonian, Basque, Ewe, Extremaduran, Faroese, Persian, Fijian, Finnish, French, Arpitan, Northern Frisian, Western Frisian, Fulah, Friulian, Gagauz, Gan Chinese, Scottish Gaelic, Irish, Galician, Gilaki, Manx, Goan Konkani, Gothic, Guarani, Gujarati, Hakka Chinese, Haitian, Hausa, Hawaiian, Serbo-Croatian, Hebrew, Herero, Fiji Hindi, Hindi, Hiri Motu, Croatian, Upper Sorbian, Hungarian, Armenian, Igbo, Ido, Inuktitut, Interlingue, Iloko, Interlingua (International Auxiliary Language Association), Indonesian, Inupiaq, Icelandic, Italian, Jamaican Creole English, Javanese, Lojban, Japanese, Kara-Kalpak, Kabyle, Kalaallisut, Kannada, Kashmiri, Georgian, Kanuri, Kazakh, Kabardian, Kabiyè, Khmer, Kikuyu, Kinyarwanda, Kirghiz, Komi-Permyak, Komi, Kongo, Korean, Karachay-Balkar, Kölsch, Kurdish, Ladino, Lao, Latin, Latvian, Lak, Lezghian, Ligurian, Limburgan, Lingala, Lithuanian, Lombard, Northern Luri, Latgalian, Luxembourgish, Ganda, Literary Chinese, Marshallese, Maithili, Malayalam, Marathi, Moksha, Eastern Mari, Minangkabau, Macedonian, Malagasy, Maltese, Mongolian, Maori, Western Mari, Malay (macrolanguage), Creek, Mirandese, Burmese, Erzya, Mazanderani, Min Nan Chinese, Neapolitan, Nauru, Navajo, Ndonga, Low German, Nepali (macrolanguage), Newari, Dutch, Norwegian Nynorsk, Norwegian, Novial, Pedi, Nyanja, Occitan (post 1500), Livvi, Oriya (macrolanguage), Oromo, Ossetian, Pangasinan, Pampanga, Panjabi, Papiamento, Picard, Pennsylvania German, Pfaelzisch, Pitcairn-Norfolk, Pali, Piemontese, Western Panjabi, Pontic, Polish, Portuguese, Pushto, Quechua, Vlax Romani, Romansh, Romanian, Rusyn, Rundi, Macedo-Romanian, Russian, Sango, Yakut, Sanskrit, Sicilian, Scots, Samogitian, Sinhala, Slovak, Slovenian, Northern Sami, Samoan, Shona, Sindhi, Somali, Southern Sotho, Spanish, Albanian, Sardinian, Sranan Tongo, Serbian, Swati, Saterfriesisch, Sundanese, Swahili (macrolanguage), Swedish, Silesian, Tahitian, Tamil, Tatar, Tulu, Telugu, Tama (Colombia), Tetum, Tajik, Tagalog, Thai, Tigrinya, Tonga (Tonga Islands), Tok Pisin, Tswana, Tsonga, Turkmen, Tumbuka, Turkish, Twi, Tuvinian, Udmurt, Uighur, Ukrainian, Urdu, Uzbek, Venetian, Venda, Veps, Vietnamese, Vlaams, Volapük, Võro, Waray (Philippines), Walloon, Wolof, Wu Chinese, Kalmyk, Xhosa, Mingrelian, Yiddish, Yoruba, Yue Chinese, Zeeuws, Zhuang, Chinese, Zulu, and Dotyali
Description:
Wikipedia plain text data obtained from Wikipedia dumps with WikiExtractor in February 2018. The data come from all Wikipedias for which dumps could be downloaded at [https://dumps.wikimedia.org/]. This amounts to 297 Wikipedias, usually corresponding to individual languages and identified by their ISO codes. Several special Wikipedias are included, most notably "simple" (Simple English Wikipedia) and "incubator" (tiny hatching Wikipedias in various languages). For a list of all the Wikipedias, see [https://meta.wikimedia.org/wiki/List_of_Wikipedias]. The script which can be used to get new version of the data is included, but note that Wikipedia limits the download speed for downloading a lot of the dumps, so it takes a few days to download all of them (but one or a few can be downloaded fast). Also, the format of the dumps changes time to time, so the script will probably eventually stop working one day. The WikiExtractor tool [http://medialab.di.unipi.it/wiki/Wikipedia_Extractor] used to extract text from the Wikipedia dumps is not mine, I only modified it slightly to produce plaintext outputs [https://github.com/ptakopysk/wikiextractor].
Rights:
Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0), http://creativecommons.org/licenses/by-sa/3.0/, and PUB

40. UDify Pretrained Model

Creator:
Kondratyuk, Dan and Straka, Milan
Publisher:
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:
tool and toolService
Subject:
syntax, dependency parser, and universal dependencies
Language:
Ancient Greek (to 1453), Arabic, Basque, Bulgarian, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Gothic, Modern Greek (1453-), Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Latin, Norwegian, Church Slavic, Persian, Polish, Portuguese, Romanian, Slovenian, Spanish, Swedish, Tamil, Catalan, Chinese, Galician, Kazakh, Latvian, Russian, Turkish, Coptic, Sanskrit, Slovak, Ukrainian, Uighur, Vietnamese, Belarusian, Korean, Lithuanian, Urdu, Russia Buriat, Northern Kurdish, Northern Sami, Upper Sorbian, Afrikaans, Yue Chinese, Marathi, Serbian, Swedish Sign Language, Telugu, Amharic, Armenian, Breton, Faroese, Komi-Zyrian, Nigerian Pidgin, Old French (842-ca. 1400), Tagalog, Thai, Warlpiri, Yoruba, Akkadian, Bambara, Erzya, and Maltese
Description:
Pretrained model weights for the UDify model, and extracted BERT weights in pytorch-transformers format. Note that these weights slightly differ from those used in the paper.
Rights:
Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), http://creativecommons.org/licenses/by-sa/4.0/, and PUB

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