Using syntactic and semantic features for classifying modal values in the Portuguese language

• Autor(a) principal: Sequeira, João
• Data de Publicação: 2016
• Outros Autores: Gonçalves, Teresa, Quaresma, Paulo, Mendes, Amália, Hendrickx, Iris
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/30783

This paper presents a study made in a eld poorly explored in the Portuguese language { modality and its automatic tagging. Our main goal was to nd a set of attributes for the creation of automatic taggers with improved performance over the bag-of-words (bow) approach. The performance was measured using precision, recall and F1. Because it is a relatively unexplored eld, the study covers the creation of the corpus (composed by eleven verbs), the use of a parser to extract syntactic and semantic information from the sentences and a machine learning approach to identify modality values. Based on three di erent sets of attributes { from trigger itself and the trigger's path (from the parse tree) and context { the system creates a tagger for each verb achieving (in almost every verb) an improvement in F1 when compared to the traditional bow approach.