Thematic Roles-Based Translation in MT Systems

The main purpose of this paper is to identify a particular thematic roles inventory that can improve the product of machine translation systems. Thematic role relations are among the semantic relations that can disambiguate the meaning of a considerable number of lexical items. Some verbs, for instance, are ambiguous for MT systems and hence are not accurately translated. The meaning of such verbs can be disambiguated by identifying the thematic role relations of their predicates. For example, ‘to express’ has two different meanings depending on its thematic role relations of its Predicate. When the verb assigns Patient <liquid> for its Object, it means ‘to squeeze out’, e.g., ‘Italians express coffee”. When it assigns Theme <letter> or <package> for its Object, it has the meaning of ‘sending by rapid transport’, e.g., ‘She expressed the letter to Florida’. The present research will focus only on a group of English verbs that convey a variety of meanings. It will show several problems in the translation of sample verbs due to the lack of thematic roles in the core of the system. 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.