Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French
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 taxonom...
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doaj-d4abd26aacf048c4b852eabb5c4103de2021-10-03T07:42:34ZengDe GruyterJournal of Intelligent Systems2191-026X2020-12-0130137639410.1515/jisys-2020-0044jisys-2020-0044Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and FrenchNazar Rogelio0Balvet Antonio1Ferraro Gabriela2Marín Rafael3Renau Irene4Pontificia Universidad Católica de Valparaíso, ValparaísoChileUniversité de Lille, LilleFranceDATA61 & Australian National University, CanberraAustraliaUniversité de Lille, LilleFrancePontificia Universidad Católica de Valparaíso, ValparaísoChileIn 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.https://doi.org/10.1515/jisys-2020-0044hypernymy detectionlanguage independent methodstaxonomy inductionunsupervised methods68w06 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nazar Rogelio Balvet Antonio Ferraro Gabriela Marín Rafael Renau Irene |
spellingShingle |
Nazar Rogelio Balvet Antonio Ferraro Gabriela Marín Rafael Renau Irene Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French Journal of Intelligent Systems hypernymy detection language independent methods taxonomy induction unsupervised methods 68w06 |
author_facet |
Nazar Rogelio Balvet Antonio Ferraro Gabriela Marín Rafael Renau Irene |
author_sort |
Nazar Rogelio |
title |
Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French |
title_short |
Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French |
title_full |
Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French |
title_fullStr |
Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French |
title_full_unstemmed |
Pruning and repopulating a lexical taxonomy: experiments in Spanish, English and French |
title_sort |
pruning and repopulating a lexical taxonomy: experiments in spanish, english and french |
publisher |
De Gruyter |
series |
Journal of Intelligent Systems |
issn |
2191-026X |
publishDate |
2020-12-01 |
description |
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. |
topic |
hypernymy detection language independent methods taxonomy induction unsupervised methods 68w06 |
url |
https://doi.org/10.1515/jisys-2020-0044 |
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