A Thematic-Role-Based Approach for Word Sense Disambiguation

Abstract

The present paper investigates the thematic roles that can be developed for the purpose of Word Sense Disambiguation. In MT systems and electronic word databases, thematic role relations are not clearly included among other semantic relations. Identifying thematic roles of predicates helps in disambiguating word senses and hence producing more accurate translation. For instance, the meaning of the verb ‘eat’ differs depending on the thematic roles it assigns for its Subject and Object. When it assigns an animate Agent for its Subject and food Patient for its Object, it means ‘take in solid food’. However, when it assigns Force for its Subject and metal Theme for its Object, it means ‘cause to deteriorate due to the action of water, air or an acid’. Accordingly, different translations are produced in each context. Selectional restrictions are also tackled in the analysis of the sample verbs. The implementation is made on three MT systems: Al Wafi, Sakhr and Google. They all produce incorrect translations of the sample verbs. A suggested translation is proposed for each verb after analyzing its thematic roles and selectional restrictions. In this way, the present paper is significant since it helps in improving the performance of MT systems. The present paper will focus only on a group of English verbs that convey a variety of meanings. It will show a number of problematic cases in translation that occur due to the lack of thematic roles in the core of the system. After developing thematic roles, it is expected that such cases will be disambiguated.