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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 ASRextractor: A Tool extracting Semantic Relations between Arabic Named Entities Ben Mesmia, Fatma; Zid, Fatma; Haddar, Kais... In: 3rd International Conference on Arabic Computational Linguistics (ACLing 2017) ; https://hal-univ-tours.archives-ouvertes.fr/hal-01632858 ; 3rd International Conference on Arabic Computational Linguistics (ACLing 2017), Nov 2017, Dubai, United Arab Emirates ; http://acling2017.org/ (2017) BASE Show details 2 Extraction of Semantic Relation between Arabic Named Entities Using Different Kinds of Transducer Cascades Ben Mesmia, Fatma; Kaouther, Bouabidi; Friburger, Nathalie; Haddar, Kais; Maurel, Denis In: 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2017) ; https://hal.archives-ouvertes.fr/hal-01491290 ; 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2017), Apr 2017, Budapest, Hungary ; http://www.cicling.org/2017/ (2017) Abstract: International audience ; The extraction of Semantic Relationship (RS) 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. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Arabic Named Entity; Arabic Wikipedia; Semantic Relation; TEI; Transducer Cas-cade URL: https://hal.archives-ouvertes.fr/hal-01491290 BASE Hide details

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