Extracting Semantic Relations between Verbs and their Arguments from Persian Texts

Extracting semantic relations between the verb and its arguments in a sentence is useful for many natural language processing applications. On the other hand the selection restrictions which a verb applies on its arguments can be used in semantic processing of texts. Manual extraction of the argument structure of verbs besides the selection restrictions of all arguments of all verbs is very time consuming as well as costly. Thus automation of this task is one of the interests of researchers in semantic text processing field. In this paper, we propose three approaches to extract semantic relations between the verb and its arguments in a sentence. The first and the simplest one is based on the morphology and the lexical analysis of words. The second approach is based on generalization and extracts the selection restrictions by statistical study of the arguments. The third approach is based on rules and generalization which labels the semantic roles besides extracting the selection restrictions. After explaining the approaches, we compare them and discuss their pros and cons.