Binary and multi-class classification of lexical functions in Spanish verb-noun collocations

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Resumen

Collocations as semi-fixed lexical combinations present a challenge in natural language processing. While collocation identification on the shallow level is a task in which a significant advance has been reached, a deeper semantic representation and analysis of collocations remains an open issue. One of the possible solutions is detection of lexical functions of the Meaning-Text Theory in collocations thus resolving their semantic interpretation. We experimented with four lexical functions (Oper1, Real1, CausFunc0, and CausFunc1) for the special case of Spanish verb-noun collocations. In our experiments we also identified free verb-noun combinations as opposed to lexical functions. We used WordNet hypernyms as features and various algorithms of supervised machine learning; the best result with an F-measure of 0.873 was achieved for detecting Oper1 in binary classification.

Idioma originalInglés
Título de la publicación alojadaAdvances in Computational Intelligence - 16th Mexican International Conference on Artificial Intelligence, MICAI 2017, Proceedings
EditoresMiguel González-Mendoza, Félix Castro, Sabino Miranda-Jiménez
EditorialSpringer Verlag
Páginas3-14
Número de páginas12
ISBN (versión impresa)9783030028398
DOI
EstadoPublicada - 2018
Evento16th Mexican International Conference on Artificial Intelligence, MICAI 2017 - Enseneda, México
Duración: 23 oct. 201728 oct. 2017

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen10633 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia16th Mexican International Conference on Artificial Intelligence, MICAI 2017
País/TerritorioMéxico
CiudadEnseneda
Período23/10/1728/10/17

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