Revista: | Computación y sistemas |
Base de datos: | PERIÓDICA |
Número de sistema: | 000395005 |
ISSN: | 1405-5546 |
Autores: | Markov, Ilia1 Mamede, Nuno2 Baptista, Jorge3 |
Instituciones: | 1Instituto Politécnico Nacional, Centro de Investigación en Computación, México, Distrito Federal. México 2Universidade de Lisboa, Instituto Superior Tecnico, Lisboa. Portugal 3Instituto de Engenharia de Sistemas e Computadores, Investigacao e Desenvolvimento em Lisboa, Laboratorio de Sistemas de Lingua Falada, Lisboa. Portugal |
Año: | 2015 |
Periodo: | Oct-Dic |
Volumen: | 19 |
Número: | 4 |
Paginación: | 661-683 |
País: | México |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Analítico |
Resumen en inglés | In this article, we improve the extraction of semantic relations between textual elements as it is currently performed by STRING, a hybrid statistical and rule-based Natural Language Processing (NLP) chain for Portuguese, by targeting whole-part relation (meronymy), that is, a semantic relation between two entities of which one is perceived as a constituent part of the other, or between a set and its member. In this case, we focus on the type of meronymy involving human entities and body-part nouns (Nbp) (e.g., O Pedro partiu uma perna 'Pedro broke a leg': WHOLE-PART (Pedro, perna) WHOLE-PART (Pedro, leg) '). In orderto extract this type of whole-part relations, a rule-based meronymy extraction module has been built and integrated in the grammar of the STRING system. The module was evaluated with promising results |
Disciplinas: | Ciencias de la computación |
Palabras clave: | Inteligencia artificial, Procesamiento de datos, Lingüística aplicada, Procesamiento de lenguaje natural, Semántica, Cuerpo humano, Meronimia, Portugués |
Keyword: | Computer science, Artificial intelligence, Data processing, Applied linguistics, Natural language processing, Semantics, Human body, Meronymy, Portuguese |
Texto completo: | Texto completo (Ver PDF) |