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Título del libro: Modern Computational Models Of Semantic Discovery In Natural Language
Título del capítulo: Extracting definitional contexts in Spanish through the identification of hyponymy-hyperonymy relations

Autores UNAM:
GERARDO EUGENIO SIERRA MARTINEZ;
Autores externos:

Idioma:
Inglés
Año de publicación:
2015
Palabras clave:

Linguistics; Statistical methods; Automatic extraction; Hyponyms; Hyponymy; Text corpora; Natural language processing systems


Resumen:

The automatic extraction of hyponymy-hypernymy relations in text corpus is one important task in Natural Language Processing. This chapter proposes a method for automatically extracting a set of hyponym-hyperonym pairs from a medical corpus in Spanish, expressed in analytical definitions. This kind of definition is composed by a term (the hyponym), a genus term (the hyperonym), and one or more differentiae, that is, a set of particular features proper to the defined term, e.g.: conjunctivitis is an infection of the conjunctiva of the eye. Definitions are obtained from definitional contexts, and then sequences of term and genus term. Then, the most frequent hyperonyms are used in order to filter relevant definitions. Additionally, using a bootstrapping technique, new hyponym candidates are extracted from the corpus, based on the previous set of hyponyms/hyperonyms detected. © 2015, IGI Global. All rights reserved.


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