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The ParlaMint corpora of parliamentary proceedings
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In: Lang Resour Eval (2022)
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Proceedings of the 17th Workshop on Multiword Expressions (MWE 2021)
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In: https://hal.archives-ouvertes.fr/hal-03320983 ; Association for Computational Linguistics. Online, 2021 (2021)
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Multilingual comparable corpora of parliamentary debates ParlaMint 2.1
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Linguistically annotated multilingual comparable corpora of parliamentary debates ParlaMint.ana 2.1
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Linguistically annotated multilingual comparable corpora of parliamentary debates ParlaMint.ana 2.0
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Multilingual comparable corpora of parliamentary debates ParlaMint 2.0
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Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic languages ...
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Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic languages ...
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Feature-Rich Named Entity Recognition for Bulgarian Using Conditional Random Fields ...
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Formae reformandae: for a reorganisation of verb form annotation in Universal Dependencies illustrated by the specific case of Latin
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Cecchini, Flavio Massimiliano (orcid:0000-0001-9029-1822). - : Association for Computational Linguistics, 2021. : country:BGR, 2021. : place:Sofia, 2021
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Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons Proceedings of the Workshop (MWE-LEX 2020)
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In: https://hal.archives-ouvertes.fr/hal-03013612 ; 2020 (2020)
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Multilingual comparable corpora of parliamentary debates ParlaMint 1.0
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The CLASSLA-StanfordNLP model for UD dependency parsing of standard Bulgarian 1.0
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Bulgarian 1.0
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Abstract:
This model for morphosyntactic annotation of standard Bulgarian was built with the CLASSLA-StanfordNLP tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the BulTreeBank training corpus (http://hdl.handle.net/11495/D93F-C6E9-65D9-2) and using the CoNLL2017 word embeddings (http://hdl.handle.net/11234/1-1989). The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~96.8.
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Keyword:
language model; part-of-speech tagging
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URL: http://hdl.handle.net/11356/1326
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