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1
Universal Dependencies 2.1
In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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2
Parsing Universal Dependencies without training
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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3
Universal Dependencies 2.0 alpha (obsolete)
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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4
Universal Dependencies 2.0
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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5
Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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6
Universal Dependencies 2.1
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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7
Baselines and test data for cross-lingual inference ...
Agić, Željko; Schluter, Natalie. - : arXiv, 2017
Abstract: The recent years have seen a revival of interest in textual entailment, sparked by i) the emergence of powerful deep neural network learners for natural language processing and ii) the timely development of large-scale evaluation datasets such as SNLI. Recast as natural language inference, the problem now amounts to detecting the relation between pairs of statements: they either contradict or entail one another, or they are mutually neutral. Current research in natural language inference is effectively exclusive to English. In this paper, we propose to advance the research in SNLI-style natural language inference toward multilingual evaluation. To that end, we provide test data for four major languages: Arabic, French, Spanish, and Russian. We experiment with a set of baselines. Our systems are based on cross-lingual word embeddings and machine translation. While our best system scores an average accuracy of just over 75%, we focus largely on enabling further research in multilingual inference. ... : To appear at LREC 2018 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1704.05347
https://dx.doi.org/10.48550/arxiv.1704.05347
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8
Universal Dependencies for Serbian in Comparison with Croatian and Other Slavic Languages ...
Samardžić, Tanja; Starović, Mirjana; Agić, Željko. - : Association for Computational Linguistic, 2017
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9
Parsing Universal Dependencies without training ...
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10
Universal Dependencies for Serbian in Comparison with Croatian and Other Slavic Languages
In: Samardžić, Tanja; Starović, Mirjana; Agić, Željko; Ljubešić, Nikola (2017). Universal Dependencies for Serbian in Comparison with Croatian and Other Slavic Languages. In: Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing, Valencia, Spain, 4 April 2017, Association for Computational Linguistic. (2017)
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