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Binary and Multi-class Classification of Lexical Functions in Spanish Verb-Noun Collocations

  • Olga Kolesnikova
  • Alexander Gelbukh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10633)

Abstract

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.

Keywords

Lexical functions Spanish verb-noun collocations Hypernyms Supervised learning 

Notes

Acknowledgements

The work was done under partial support of Mexican Government: SNI, BEIFI-IPN, and SIP-IPN grants 20172044 and 20172008.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Escuela Superior de CómputoInstituto Politécnico NacionalMexico CityMexico
  2. 2.Centro de Investigación en ComputaciónInstituto Politécnico NacionalMexico CityMexico

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