Extracting HPSG Lexicon from Arabic VerbNet

This paper presents the construction of a HPSG lexicon of Arabic verbal entities, automatically inferred from the Arabic VerbNet, a large coverage verb lexicon where verbs are classified using syntactic alternations. We discuss the main verb specification along with the relation of the syntactic and semantic levels of representation within the HPSG framework. Extensive analysis of the Arabic VerbNet classes has led to the adoption of a finite set of mapping rules between AVN classes and HPSG subcategorization and semantics descriptions covering the majority of the verbal tokens. We employed the adopted mapping rules to extract the syntactic and semantic data from AVN and finally, we describe the resulting TDL descriptions in which the lexicon has been encoded.