Automatic lexical collocate extraction for corpus-based ontology building and refinementA FunGramKB case study of the THEFT conceptual scenario

  1. Nicolás José Fernández-Martínez
  2. Ángel Miguel Felices-Lago
Revista:
Revista española de lingüística aplicada

ISSN: 0213-2028

Año de publicación: 2021

Volumen: 34

Número: 2

Páginas: 435-463

Tipo: Artículo

DOI: 10.1075/RESLA.19030.FER DIALNET GOOGLE SCHOLAR

Otras publicaciones en: Revista española de lingüística aplicada

Objetivos de desarrollo sostenible

Resumen

Traditional corpus-based methods rely on manual inspection and extraction of lexical collocates in the study of selection preferences, which is a very costly, labor-intensive, and time-consuming task. Devising automatic methods for lexical collocate extraction becomes necessary to handle this task and the immensity of corpora available. With a view to leveraging the Sketch Engine platform and in-built corpora, we propose a working prototype of a Lexical Collocate Extractor (LeCoExt) command-line tool that mines lexical collocates from all types of verbs according to their syntactic constituents and Collocate Frequency Score (CFS). This might be the first tool that performs comprehensive corpus-based studies of the selection preferences of individual or groups of verbs exploiting the capabilities offered by Sketch Engine. This tool might facilitate the task of extracting rich lexico-semantic knowledge from diverse corpora in a few seconds and at a click away. We test its performance for ontology building and refinement departing from a previous detailed analysis of stealing verbs carried out by Fernández-Martínez & Faber (2020). We show how the proposed tool is used to extract conceptual-cognitive knowledge from the THEFT scenario and implement it into FunGramKB Core Ontology through the creation and modification of theft-related conceptual units.

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Información de financiación

This article is based on the R&D Project within the framework of the ?Programa Operativo FEDER Andaluc?a 2014-2020 (code B-HUM177-UGR18)? and funded by Junta de Andaluc?a, Spain.

Financiadores

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