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21
Multitask Easy-First Dependency Parsing ...
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22
Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling ...
Zalmout, Nasser; Habash, Nizar. - : arXiv, 2019
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23
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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24
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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25
Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging ...
Zalmout, Nasser; Habash, Nizar. - : arXiv, 2019
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26
CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing
In: 11th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-01786125 ; 11th Language Resources and Evaluation Conference, May 2018, Miyazaki, Japan ; http://lrec2018.lrec-conf.org (2018)
Abstract: International audience ; Following the development of the universal dependencies (UD) framework and the CoNLL 2017 Shared Task on end-to-end UD parsing, we address the need for a universal representation of morphological analysis which on the one hand can capture a range of different alternative morphological analyses of surface tokens, and on the other hand is compatible with the segmentation and morphological annotation guidelines prescribed for UD treebanks. We propose the CoNLL universal lattices (CoNLL-UL) format, a new annotation format for word lattices that represent morphological analyses, and provide resources that obey this format for a range of typologically different languages. The resources we provide are harmonized with the two-level representation and morphological annotation in their respective UD v2 treebanks, thus enabling research on universal models for morphological and syntactic parsing , in both pipeline and joint settings, and presenting new opportunities in the development of UD resources for low-resource languages.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Morphological Ambiguity; Morphological Analysis; Morphology; Universal Dependencies
URL: https://hal.inria.fr/hal-01786125/file/more2018.pdf
https://hal.inria.fr/hal-01786125
https://hal.inria.fr/hal-01786125/document
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27
Universal Dependencies 2.2
In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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28
MADARi: A Web Interface for Joint Arabic Morphological Annotation and Spelling Correction ...
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29
Universal Dependencies 2.3
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
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30
Universal Dependencies 2.2
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
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31
Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models ...
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32
Identifying effective translations for cross-lingual Arabic-to-English user-generated speech search
In: Khwileh, Ahmad, Afli, Haithem orcid:0000-0002-7449-4707 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 and Way, Andy orcid:0000-0001-5736-5930 (2017) Identifying effective translations for cross-lingual Arabic-to-English user-generated speech search. In: Third Arabic Natural Language Processing Workshop (WANLP), 3 Apr 2017, Valencia, Spain. (2017)
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33
Universal Dependencies 2.1
In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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34
Universal Dependencies 2.0 alpha (obsolete)
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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35
Universal Dependencies 2.0
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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36
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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37
Universal Dependencies 2.1
Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017
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38
Low Resourced Machine Translation via Morpho-syntactic Modeling: The Case of Dialectal Arabic ...
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39
CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Çöltekin, Çağrı; Kayadelen, Tolga; Droganova, Kira. - : Association for Computational Linguistics, 2017. : country:USA, 2017. : place:Stroudsburg, PA, 2017
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40
Optimizing Tokenization Choice for Machine Translation across Multiple Target Languages
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 257-269 (2017) (2017)
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