Inconsistencies Detection in Bipolar Entailment Graphs

Elena Cabrio 1 Serena Villata 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Résumé : English. In the latest years, a number of real world applications have underlined the need to move from Textual Entailment (TE) pairs to TE graphs where pairs are no more independent. Moving from single pairs to a graph has the advantage of providing an overall view of the issue discussed in the text, but this may lead to possible inconsistencies due to the combination of the TE pairs into a unique graph. In this paper, we adopt argumentation theory to support human annotators in detecting the possible sources of inconsistencies. Italiano. Negli ultimi anni, in svari-ate applicazioni sta sorgendo la necessit a di passare da coppie di Textual Entail-ment (TE) a grafi di TE, in cui le cop-pie sono interconnesse. Il vantaggio dei grafi di TE e di fornire una visione glob-ale del soggetto di cui si sta discutendo nel testo. Allo stesso tempo, questopù o gener-are inconsistenze dovute all'integrazione dipì u coppie di TE in un unico grafo. In questo articolo, ci basiamo sulla teo-ria dell'argomentazione per supportare gli annotatori nell'individuare le possibili fonti di inconsistenze.
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Conference papers
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https://hal.inria.fr/hal-01236707
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Submitted on : Wednesday, December 2, 2015 - 10:23:46 AM
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Elena Cabrio, Serena Villata. Inconsistencies Detection in Bipolar Entailment Graphs. Second Italian Conference on Computational Linguistics - CLiC-it 2015, Dec 2015, Trento, Italy. ⟨hal-01236707⟩

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