Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Manon Scholivet"'
Publikováno v:
NAACL-HLT (1)
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Jun 2019, Minneapolis, United States. pp.3919-3930, ⟨10.18653/v1/N19-1393⟩
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Jun 2019, Minneapolis, United States. pp.3919-3930, ⟨10.18653/v1/N19-1393⟩
International audience; The existence of universal models to describe the syntax of languages has been debated for decades. The availability of resources such as the Universal Dependencies treebanks and the World Atlas of Language Structures make it
We present a simple and efficient sequence tagger capable of identifying continuous multiword expressions (MWEs) of several categories in French texts. It is based on conditional random fields (CRF), using as features local context information such a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::524cd2000356c8e13917db130e9fc18e
Autor:
Carlos Ramisch, Manon Scholivet
Publikováno v:
MWE@EACL
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017), 2017, Valencia, Spain. pp.167-175
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017), 2017, Valencia, Spain. pp.167-175
International audience; We present a simple and efficient tagger capable of identifying highly ambiguous multiword expressions (MWEs) in French texts. It is based on conditional random fields (CRF), using local context information as features. We sho