Multiword Expressions (MWEs) raise an important problem for the development of largescale NLP systems. The lack of compositionality of the semantics of these expressions has led some researchers to simply list them in the lexicon. However, the components of many MWEs can be separated from each other by intervening material in syntax and are often missed by systems that treat these expressions as single units. In this paper, we will focus on one genre of multiword expressions, namely the light verb constructions (LVCs) in Persian.
We argue that the latest developments in analyzing these complex verbal predicates along with the linguistic research performed on Persian light verb constructions can shed some light on a successful computational modeling of multilingual complex predicates in general, and on Persian light verb constructions in particular. The approach proposed here is based on the lexical semantic representation of verbal predicates by providing a template that reflects the combination of the various primitive components and the realization of the verb's argument structure in syntax. By extending the research described in Fong et al (2000) to Persian verbal constructions, we propose to map the semantic templates as an interlingual representation. It is argued that this approach, which is based on the recent linguistic research, can provide a more efficient NLP system in the long run and will facilitate multilingual computational applications.