ASRextractor: A Tool extracting Semantic Relations between Arabic Named Entities

Since the MUC-7, the extraction of the Semantic Relation (SR) extraction has been started aiming to detect the significant links between Named Entities (NEs). This task is evolved in many domains to realize several objectives such as corpora and electronic NE dictionary enrichment. In this context,...

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Bibliographic Details
Published in:Procedia computer science 2017, Vol.117, p.55-62
Main Authors: Mesmia, Fatma Ben, Zid, Fatma, Haddar, Kais, Maurel, Denis
Format: Article
Language:English
Subjects:
Arabic Named Entity
Arabic Wikipedia
Semantic Relation
TEI recommendation
transducer casacde
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Summary:Since the MUC-7, the extraction of the Semantic Relation (SR) extraction has been started aiming to detect the significant links between Named Entities (NEs). This task is evolved in many domains to realize several objectives such as corpora and electronic NE dictionary enrichment. In this context, we propose a rue-based system called ASRextractor, which extracts and annotates SRs relating Arabic NEs (ANEs). The SR extraction is based on an annotated Arabic Wikipedia corpus and it helps us identify 18 SR types such as synonymy and origin. For the SR annotation, our proposed system reposes on an annotation syntax respecting the TEI (Text Encoding Initiative) recommendation. Moreover, ASRextractor is based on finite state transducers, which ensure both the extraction and annotation process. The established transducers are regrouped inside an analysis cascade in a predefined order. The metric values show that our obtained results are encouraging.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2017.10.123