Lexical Function Identification Using Word Embeddings and Deep Learning

Arturo Hernández-Miranda, Alexander Gelbukh, Olga Kolesnikova

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we report the results of our experiments on the task of distinguishing the semantics of verb-noun collocations in a Spanish corpus. This semantics was represented by four lexical functions of the Meaning-Text Theory. Each lexical function specifies a certain universal semantic concept found in any natural language. Knowledge of collocation and its semantic content is important for natural language processing, as collocation comprises the restrictions on how words can be used together. We experimented with a combination of GloVe word embeddings as a recent and extended algorithm for vector representation of words and a deep neural architecture, in order to recover most of the context of verb-noun collocations in a meaningful way which could discriminate among lexical functions. Our corpus was a collection of 1,131 Excelsior newspaper issues. As our results showed, the proposed deep neural architecture outperformed state-of-the-art supervised learning methods.

Original languageEnglish
Title of host publicationAdvances in Soft Computing - 18th Mexican International Conference on Artificial Intelligence, MICAI 2019, Proceedings
EditorsLourdes Martínez-Villaseñor, Ildar Batyrshin, Antonio Marín-Hernández
PublisherSpringer
Pages77-86
Number of pages10
ISBN (Print)9783030337483
DOIs
StatePublished - 1 Jan 2019
Event18th Mexican International Conference on Artificial Intelligence, MICAI 2019 - Xalapa, Mexico
Duration: 27 Oct 20192 Nov 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11835 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th Mexican International Conference on Artificial Intelligence, MICAI 2019
Country/TerritoryMexico
CityXalapa
Period27/10/192/11/19

Keywords

  • Deep learning
  • Lexical function
  • Meaning-Text Theory
  • Word embeddings

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