ASRextractor: A Tool extracting Semantic Relations between Arabic Named Entities

Abstract : 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.
Type de document :
Communication dans un congrès
3rd International Conference on Arabic Computational Linguistics (ACLing 2017), Nov 2017, Dubai, United Arab Emirates. 2017, 〈http://acling2017.org/〉
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https://hal-univ-tours.archives-ouvertes.fr/hal-01632858
Contributeur : Denis Maurel <>
Soumis le : vendredi 10 novembre 2017 - 16:28:57
Dernière modification le : jeudi 17 mai 2018 - 14:44:12

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  • HAL Id : hal-01632858, version 1

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Fatma Ben Mesmia, Fatma Zid, Kais Haddar, Denis Maurel. ASRextractor: A Tool extracting Semantic Relations between Arabic Named Entities. 3rd International Conference on Arabic Computational Linguistics (ACLing 2017), Nov 2017, Dubai, United Arab Emirates. 2017, 〈http://acling2017.org/〉. 〈hal-01632858〉

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