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Towards Instance-Level Parser Selection for Cross-Lingual Transfer of Dependency Parsers
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Glavas, Goran; Agic, Zeljko; Vulic, Ivan. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.345, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020
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9 |
Universal Dependencies 2.2
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In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging ...
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The Best of Both Worlds: Lexical Resources To Improve Low-Resource Part-of-Speech Tagging ...
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hr500k – A Reference Training Corpus of Croatian.
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In: Conference papers (2018)
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Universal Dependencies 2.1
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In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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17 |
Parsing Universal Dependencies without training
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In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, ; EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01677405 ; EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2017, Valencia, Spain. pp.229 - 239 ; http://eacl2017.org/ (2017)
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Abstract:
International audience ; We propose UDP, the first training-free parser for Universal Dependencies (UD). Our algorithm is based on PageRank and a small set of head attachment rules. It features two-step decoding to guarantee that function words are attached as leaf nodes. The parser requires no training, and it is competitive with a delexicalized transfer system. UDP offers a linguistically sound unsupervised alternative to cross-lingual parsing for UD, which can be used as a baseline for such systems. The parser has very few parameters and is distinctly robust to domain change across languages.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.inria.fr/hal-01677405 https://hal.inria.fr/hal-01677405/file/alonso2017-parsing.pdf https://hal.inria.fr/hal-01677405/document
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Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
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