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Ambiguity Diagnosis for Terms in Digital Humanities

Béatrice Daille 1 Evelyne Jacquey 2 Gaël Lejeune 3 Luis Felipe Melo 4 Yannick Toussaint 4 
LINA - Laboratoire d'Informatique de Nantes Atlantique
4 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Among all researches dedicating to terminology and word sense disambiguation, little attention has been devoted to the ambiguity of term occurrences. If a lexical unit is indeed a term of the domain, it is not true, even in a specialised corpus, that all its occurrences are terminological. Some occurrences are terminological and other are not. Thus, a global decision at the corpus level about the terminological status of all occurrences of a lexical unit would then be erroneous. In this paper, we propose three original methods to characterise the ambiguity of term occurrences in the domain of social sciences for French. These methods differently model the context of the term occurrences: one is relying on text mining, the second is based on textometry, and the last one focuses on text genre properties. The experimental results show the potential of the proposed approaches and give an opportunity to discuss about their hybridisation.
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Submitted on : Friday, December 30, 2016 - 6:30:28 PM
Last modification on : Tuesday, October 25, 2022 - 4:22:39 PM
Long-term archiving on: : Tuesday, March 21, 2017 - 6:10:35 AM


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  • HAL Id : hal-01423650, version 1


Béatrice Daille, Evelyne Jacquey, Gaël Lejeune, Luis Felipe Melo, Yannick Toussaint. Ambiguity Diagnosis for Terms in Digital Humanities. Language Resources and Evaluation Conference, May 2016, Portorož, Slovenia. ⟨hal-01423650⟩



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