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Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing
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In: https://hal.archives-ouvertes.fr/hal-01856176 ; 2018 (2018)
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SEx BiST: A Multi-Source Trainable Parser with Deep Contextualized Lexical Representations
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In: Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies ; https://hal.archives-ouvertes.fr/hal-02977455 ; Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Oct 2018, Bruxelles, Belgium. pp.143-152, ⟨10.18653/v1/K18-2014⟩ ; https://www.conll.org/2018/ (2018)
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Multilingual Dependency Parsing for Low-Resource Languages: Case Studies on North Saami and Komi-Zyrian
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In: LREC 2018 Proceedings ; Language Resource and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-01856178 ; Language Resource and Evaluation Conference, ELRA, May 2018, Miyazaki, Japan ; http://www.lrec-conf.org/proceedings/lrec2018/pdf/600.pdf (2018)
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Dependency Parsing of Code-Switching Data with Cross-Lingual Feature Representations
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In: International Workshop on Computational Linguistics for Uralic Languages ; https://hal.archives-ouvertes.fr/hal-01722243 ; International Workshop on Computational Linguistics for Uralic Languages, Jan 2018, Helsinki, Finland. pp.1 - 17 ; aclweb.org/anthology/W18-0200 (2018)
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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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Language, Cognition, and Computational Models
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In: https://hal.archives-ouvertes.fr/hal-01722351 ; Cambridge University Press, 2018 ; https://www.cambridge.org/core/books/language-cognition-and-computational-models/90CC7DBA6CADB1FE361266D311CB4413 (2018)
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Introduction: Cognitive Issues in Natural Language Processing
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In: Language, Cognition, and Computational Models ; https://hal.archives-ouvertes.fr/hal-01722353 ; Language, Cognition, and Computational Models, Cambridge University Press, 2018, 9781316676974 ; https://doi.org/10.1017/9781316676974 (2018)
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Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing ...
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Abstract:
Linguistic typology aims to capture structural and semantic variation across the world's languages. A large-scale typology could provide excellent guidance for multilingual Natural Language Processing (NLP), particularly for languages that suffer from the lack of human labeled resources. We present an extensive literature survey on the use of typological information in the development of NLP techniques. Our survey demonstrates that to date, the use of information in existing typological databases has resulted in consistent but modest improvements in system performance. We show that this is due to both intrinsic limitations of databases (in terms of coverage and feature granularity) and under-employment of the typological features included in them. We advocate for a new approach that adapts the broad and discrete nature of typological categories to the contextual and continuous nature of machine learning algorithms used in contemporary NLP. In particular, we suggest that such approach could be facilitated by ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1807.00914 https://dx.doi.org/10.48550/arxiv.1807.00914
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Dependency Parsing of Code-Switching Data with Cross-Lingual Feature Representations
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In: International Workshop on Computational Linguistics for Uralic languages. - Helsinki, ISBN: (2018)
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Rating Distributions and Bayesian Inference. Enhancing Cognitive Models of Spatial Language Use
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