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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 Page: 1 2 Hits 1 – 20 of 22 1 BUSINESS MEETING ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bender, Emily M.; Callison-Burch, Chris. - : Underline Science Inc., 2021 BASE Show details 2 MassiveSumm: a very large-scale, very multilingual, news summarisation dataset ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Schluter, Natalie; Varab, Daniel. - : Underline Science Inc., 2021 BASE Show details 3 SemEval-2021 Task 12: Learning with Disagreements Uma, Alexandra; Fornaciari, Tommaso; Dumitrache, Anca. - : Association for Computational Linguistics, 2021 BASE Show details 4 IAPUCP at SemEval-2021 task 1: Stacking fine-tuned transformers is almost all you need for lexical complexity prediction Rivas Rojas, Kervy; Alva-Manchego, Fernando. - : Association for Computational Linguistics, 2021 BASE Show details 5 Speakers Enhance Contextually Confusable Words Meinhardt, Eric; Bakovic, Eric; Bergen, Leon. - : eScholarship, University of California, 2020 BASE Show details 6 Predicting Declension Class from Form and Meaning Cotterell, Ryan; Blix, Hagen; Pimentel, Tiago... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 7 The Paradigm Discovery Problem Wu, Shijie; Habash, Nizar; Elsner, Micha... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 8 A Tale of a Probe and a Parser Valvoda, Josef; Hall Maudslay, Rowan; Williams, Adina... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 9 A Corpus for Large-Scale Phonetic Typology Chodroff, Eleanor; Cotterell, Ryan; Wiesner, Matthew... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 10 Information-Theoretic Probing for Linguistic Structure Pimentel, Tiago; Zmigrod, Ran; Cotterell, Ryan... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 11 It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information Mielke, Sabrina J.; Okazaki, Naoaki; Anastasopoulos, Antonios... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 12 ASSET: A dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations Alva Manchego, Fernando; Martin, Louis; Bordes, Antoine. - : ACL, 2020 BASE Show details 13 Non-linear instance-based cross-lingual mapping for non-isomorphic embedding spaces Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2020 BASE Show details 14 Classification-based self-learning for weakly supervised bilingual lexicon induction Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020 BASE Show details 15 On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020 BASE Show details 16 Baselines and test data for cross-lingual inference ... Agić, Željko; Schluter, Natalie. - : arXiv, 2017 BASE Show details 17 Multilingual Projection for Parsing Truly Low-Resource Languageš Agic, Zeljko; Johannsen, Anders; Plank, Barbara... 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) BASE Show details 18 Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources Schluter, Natalie. - : Dublin City University. National Centre for Language Technology (NCLT), 2011. : Dublin City University. School of Computing, 2011 In: Schluter, Natalie (2011) Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources. PhD thesis, Dublin City University. (2011) BASE Show details 19 Dependency parsing resources for French: Converting acquired lexical functional grammar F-Structure annotations and parsing F-Structures directly Schluter, Natalie; van Genabith, Josef In: Schluter, Natalie and van Genabith, Josef orcid:0000-0003-1322-7944 (2009) Dependency parsing resources for French: Converting acquired lexical functional grammar F-Structure annotations and parsing F-Structures directly. In: Nodalida 2009 Conference, 14 - 16 May 2009, Odense, Denmark. (2009) BASE Show details 20 Treebank-based acquisition of LFG parsing resources for French Schluter, Natalie; van Genabith, Josef In: Schluter, Natalie and van Genabith, Josef (2008) Treebank-based acquisition of LFG parsing resources for French. In: the Sixth International Language Resources and Evaluation Conference (LREC'08), May 28-30, 2008, Marrakech, Morocco. (2008) Abstract: Motivated by the expense in time and other resources to produce hand-crafted grammars, there has been increased interest in automatically obtained wide-coverage grammars from treebanks for natural language processing. In particular, recent years have seen the growth in interest in automatically obtained deep resources that can represent information absent from simple CFG-type structured treebanks and which are considered to produce more language-neutral linguistic representations, such as dependency syntactic trees. As is often the case in early pioneering work on natural language processing, English has provided the focus of first efforts towards acquiring deep-grammar resources, followed by successful treatments of, for example, German, Japanese, Chinese and Spanish. However, no comparable large-scale automatically acquired deep-grammar resources have been obtained for French to date. The goal of this paper is to present the application of treebank-based language acquisition to the case of French. We show that with modest changes to the established parsing architectures, encouraging results can be obtained for French, with a best dependency structure f-score of 86.73%. Keyword: Lexical Functional Grammars; LFG; Machine translating URL: http://doras.dcu.ie/16176/ BASE Hide details Page: 1 2

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