Autores
Kolesnikova Olga
Gelbukh Alexander
Chanona Hernández Liliana
Título Automatic Detection of Semantic Classes of Verb-Noun Collocations
Tipo Revista
Sub-tipo CONACYT
Descripción Computación y Sistemas
Resumen It does not surprise us that a bank can be a financial institution as well as a piece of land. Quite often one word is used with different meanings. But sometimes the opposite happens: we choose different words to express the same idea. For example, to give a smile means 'to smile', and to lend support means 'to support' (Longman Dictionary of Contemporary English, 1995). These two collocations convey the same idea: to smile is to 'perform', or 'do' a smile, and to support is to 'do' support, so that both verb-noun collocations share the same semantics: to do what is denoted by the noun. Likewise, we find that to acquire popularity and to sink into despair both mean 'to begin to experience the ', and to establish a relation and to find a solution mean 'to create the '. Such semantic patterns or classes are called lexical functions. In this article, we explain the concept of lexical functions, give a summary of state-of-the-art research on automatic detection of lexical functions, and present the framework and results of our experiments on supervised learning of lexical functions fulfilled on the material of Spanish verb-noun collocations.
Observaciones DOI 10.13053/CyS-24-1-3130
Lugar Ciudad de México
País Mexico
No. de páginas 141-150
Vol. / Cap. v. 24 no. 1
Inicio 2020-06-01
Fin
ISBN/ISSN