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Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French

Abstract : In this paper we present the problem of a noisy lexical taxonomy and suggest two tasks as potential remedies. The first task is to identify and eliminate incorrect hypernymy links, and the second is to repopulate the taxonomy with new relations. The first task consists of revising the entire taxonomy and returning a Boolean for each assertion of hypernymy between two nouns (e.g. brie is a kind of cheese). The second task consists of recursively producing a chain of hypernyms for a given noun, until the most general node in the taxonomy is reached (e.g. brie → cheese → food → etc.). In order to achieve these goals, we implemented a hybrid hypernym-detection algorithm that incorporates various intuitions, such as syntagmatic, paradigmatic and morphological association measures as well as lexical patterns. We evaluate these algorithms individually and collectively and report findings in Spanish, English and French.
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Contributor : Antonio Balvet <>
Submitted on : Tuesday, December 1, 2020 - 12:11:18 PM
Last modification on : Saturday, December 26, 2020 - 11:28:02 AM
Long-term archiving on: : Tuesday, March 2, 2021 - 7:01:48 PM


[2191026X - Journal of Intelli...
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Rogelio Nazar, Antonio Balvet, Gabriela Ferraro, Rafael Marín, Irene Renau. Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French. Journal of Intelligent Systems, Walter de Gruyter, 2020, ⟨10.1515/jisys-2020-0044⟩. ⟨halshs-03033309⟩



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