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Load What You Need: Smaller Versions of Multilingual BERT ...
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Composition of Embeddings : Lessons from Statistical Relational Learning
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In: Proceedings of SEM 2019 ; 8th Joint Conference on Lexical and Computational Semantics (SEM 2019) ; https://hal.archives-ouvertes.fr/hal-02397476 ; 8th Joint Conference on Lexical and Computational Semantics (SEM 2019), Jun 2019, Minneapolis, United States. pp.33-43 (2019)
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Mining Discourse Markers for Unsupervised Sentence Representation Learning
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In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2019) ; https://hal.archives-ouvertes.fr/hal-02397473 ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2019), Jun 2019, Minneapolis, United States. pp.3477-3486 (2019)
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Système d’ensemble pour la classification de tweets, DEFT 2017
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In: Atelier Défi Fouille de Textes : Analyse d'opinion et langage figuratif dans des tweets en français@ TALN/RECITAL 2017 (DEFT 2017) ; https://hal.archives-ouvertes.fr/hal-03120281 ; Atelier Défi Fouille de Textes : Analyse d'opinion et langage figuratif dans des tweets en français@ TALN/RECITAL 2017 (DEFT 2017), Jun 2017, Orléans, France. pp.27-31 ; http://talnarchives.atala.org/ateliers/2017/DEFT/2.pdf (2017)
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SWIP at QALD-3 : results, criticisms and lesson learned
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In: QALD-3 : Multilingual Question Answering over Linked Data ; 3rd open challenge on Question Answering over Linked Data (QALD 2013) ; https://hal.archives-ouvertes.fr/hal-01193095 ; 3rd open challenge on Question Answering over Linked Data (QALD 2013), Sep 2013, Valencia, Spain. pp. 1-13 (2013)
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Abstract:
International audience ; This paper presents the results obtained by the SWIP system while participating in the QALD-3 (Question Answering over Linked Data) challenge, co-located with CLEF 2013 (Conference and Labs of the Evaluation Forum). We tackled task 1, multilingual question answering, whose purpose is to interpret natural language questions in order to return the answers contained in a graph knowledge base. We answered queries of both proposed datasets (one concerning DBpedia, the other Musicbrainz) and took into consideration only questions in English. The system SWIP (Semantic Web Interface using Patterns) aims at automatically generating formal queries from user queries expressed in natural language. For this, it relies on the use of query patterns which enable the complex task of interpreting natural language queries. The results obtained on the Musicbrainz dataset (precision = 0,51, recall = 0,51, F-measure = 0,51) are very satisfactory and encouraging. The results on DBpedia (precision = 0,16, recall = 0,15, F-measure = 0,16) are more disappointing. In this paper, we present both the SWIP approach and its implementation. We then present the results of the challenge in more detail and their analysis. Finally we draw some conclusions on the strengths and weaknesses of our approach, and suggest ways to improve its performance.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]; Semantic Web Interface using Patterns; SWIP
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URL: https://hal.archives-ouvertes.fr/hal-01193095/document
https://hal.archives-ouvertes.fr/hal-01193095/file/pradel_12892.pdf
https://hal.archives-ouvertes.fr/hal-01193095
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