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Universal Dependencies 2.2
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In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat ...
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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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Abstract:
In natural language processing, the deep learning revolution has shifted the focus from conventional hand-crafted symbolic representations to dense inputs, which are adequate representations learned automatically from corpora. However, particularly when working with low-resource languages, small amounts of symbolic lexical resources such as user-generated lexicons are often available even when gold-standard corpora are not. Such additional linguistic information is though often neglected, and recent neural approaches to cross-lingual tagging typically rely only on word and subword embeddings. While these representations are effective, our recent work has shown clear benefits of combining the best of both worlds: integrating conventional lexical information improves neural cross-lingual part-of-speech (PoS) tagging. However, little is known on how complementary such additional information is, and to what extent improvements depend on the coverage and quality of these external resources. This paper seeks to ... : Under review for Natural Language Engineering ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1811.08757
https://arxiv.org/abs/1811.08757
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| 27 |
Bleaching Text: Abstract Features for Cross-lingual Gender Prediction ...
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| 28 |
Universal Dependencies 2.1
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In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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When is multitask learning effective? Semantic sequence prediction under varying data conditions
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In: EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01677427 ; EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2017, Valencia, Spain. pp.1-10 ; http://eacl2017.org/ (2017)
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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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| 33 |
Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
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ALL-IN-1: Short Text Classification with One Model for All Languages ...
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| 37 |
Multilingual Projection for Parsing Truly Low-Resource Languageš
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01426754 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2016 (2016)
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Supersense tagging with inter-annotator disagreement
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In: Linguistic Annotation Workshop 2016 ; https://hal.inria.fr/hal-01426747 ; Linguistic Annotation Workshop 2016, Aug 2016, Berlin, Germany. pp.43 - 48 (2016)
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