Harnessing Open Information Extraction for Entity Classification in a French Corpus
| Titre | Harnessing Open Information Extraction for Entity Classification in a French Corpus |
| Type de publication | Conference Paper |
| Année de publication | 2016 |
| Auteurs | Gotti, F., and P. Langlais |
| Nom de la conférence | Canadian AI 2016 |
| Éditeur | Springer International Publishing Switzerland |
| Mots-clés | Entity classification, Named entities, Natural language processing, Open information extraction |
| Résumé | We describe a recall-oriented open information extraction system designed to extract knowledge from French corpora. We put it to the test by showing that general domain information triples (extracted from French Wikipedia) can be used for deriving new knowledge from domain-specific documents unrelated to Wikipedia. Specifically, we can label entity instances extracted in one corpus with the entity types identified in the other, with little supervision. We believe that the present study is the first one that focusses on such a cross-domain, recall-oriented approach in open information extraction. |
| Refereed Designation | Refereed |
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