An Automated Thematic Role Labeler and Generalizer for Filipino Verb Arguments

PACLIC 23 / City University of Hong Kong / 3-5 December 200

An automated thematic role labeler and generalizer for Filipino verb arguments

A lexicon is an essential resource in the Natural Language Processing research. It provides the link between the terms of a language and the semantic and syntactic properties they are associated with. For the Filipino language, only bilingual and multilingual lexicons are available electronically. Generally, the only information they contain are the translations of a term from one language to another. They do not have information on thematic roles, which are the relations of verbs and their arguments. These relations are useful because they could allow systems to check whether the required arguments are present in the sentence. To augment manual entries of the thematic roles into the lexicon, automatic learning of thematic roles of verb arguments is explored. This paper presents the resources needed, the processes, and the results. © 2009 by Briane Paul Samson Bianca Pamela Alcera, Ed Oswald Go, Czarina Meg Gonzales, and Nathalie Rose Lim