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

Author:

Nazar Rogelio1,Balvet Antonio2,Ferraro Gabriela3,Marín Rafael2,Renau Irene1

Affiliation:

1. Pontificia Universidad Católica de Valparaíso , Valparaíso Chile

2. Université de Lille , Lille France

3. DATA61 & Australian National University , Canberra Australia

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Artificial Intelligence,Information Systems,Software

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