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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 ELMoLex: Connecting ELMo and Lexicon features for Dependency Parsing Jawahar, Ganesh; Muller, Benjamin; Fethi, Amal; Martin, Louis; Villemonte de La Clergerie, Éric; Sagot, Benoît; Seddah, Djamé In: CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies ; https://hal.inria.fr/hal-01959045 ; CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, Oct 2018, Brussels, Belgium. ⟨10.18653/v1/K18-2023⟩ (2018) Abstract: International audience ; In this paper, we present the details of the neural dependency parser and the neu-ral tagger submitted by our team 'ParisNLP' to the CoNLL 2018 Shared Task on parsing from raw text to Universal Dependencies. We augment the deep Biaffine (BiAF) parser (Dozat and Manning, 2016) with novel features to perform competitively: we utilize an indomain version of ELMo features (Peters et al., 2018) which provide context-dependent word representations; we utilize disambiguated, embedded, morphosyntactic features from lexicons (Sagot, 2018), which complements the existing feature set. Henceforth , we call our system 'ELMoLex'. In addition to incorporating character embed-dings, ELMoLex leverage pre-trained word vectors, ELMo and morphosyntactic features (whenever available) to correctly handle rare or unknown words which are prevalent in languages with complex morphology. ELMoLex 1 ranked 11th by Labeled Attachment Score metric (70.64%), Morphology-aware LAS metric (55.74%) and ranked 9th by Bilexical dependency metric (60.70%). In an extrinsic evaluation setup, ELMoLex ranked 7 th for Event Extraction, Negation Resolution tasks and 11th for Opinion Analysis task by F1 score. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] URL: https://hal.inria.fr/hal-01959045/document https://hal.inria.fr/hal-01959045 https://hal.inria.fr/hal-01959045/file/elmolex-connecting-elmo.pdf https://doi.org/10.18653/v1/K18-2023 BASE Hide details 2 Cheating a Parser to Death: Data-driven Cross-Treebank Annotation Transfer Seddah, Djamé; Villemonte de La Clergerie, Éric; Sagot, Benoît... In: Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ; https://hal.inria.fr/hal-01798801 ; Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, Miyazaki, Japan (2018) BASE Show details 3 CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing More, Amir; Çetinoğlu, Özlem; Çöltekin, Çağri... 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) BASE Show details 4 Universal Dependencies 2.3 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 5 CoNLL 2018 Shared Task System Outputs Zeman, Daniel; Potthast, Martin; Duthoo, Elie. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2018 BASE Show details

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