Extraction of semantic relation between arabic named entities using different kinds of transducer cascades

Abstract

The extraction of Semantic Relationship (SR) is an important task allowing the identification of relevant semantic information in the annotated textual resources. Besides, extracting SR between Named Entities (NE) is a process, which consists in guessing the significant semantic links related to them. This process is very useful to enhance the NLP-application performance, such as Question Answering systems. In this paper, we propose a rule-based method to extract and annotate SR between Arabic NEs (ANE) using an annotated Arabic Wikipedia corpus. In fact, our proposed method is composed of two main cascades regrouping respectively analysis and synthesis transducers. The analysis transducer cascade is dedicated to extract five SR types, which are synonymy, meronymy, accessibility, functional and proximity. However, synthesis one is devoted to normalize the SR and NE annotation using the TEI (Text Encoding Initiative) recommendation. Furthermore, the established transducer cascades are implemented and generated using the CasSys tool available under Unitex linguistic platform. Finally, the obtained results showed by the calculated measure values are encouraging.