Impact of Entity Graphs on Extracting Semantic Relations

Rashedur Rahman 1, 2 Brigitte Grau Sophie Rosset
1 LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur
2 IRT SystemX - IRT SystemX
Abstract : Relation extraction (RE) between a pair of entity mentions from text is an important and challenging task specially for open domain relations. Generally, relations are extracted based on the lexical and syntactical information at the sentence level. However, global information about known entities has not been explored yet for RE task. In this paper, we propose to extract a graph of entities from the overall corpus and to compute features on this graph that are able to capture some evidences of holding relationships between a pair of entities. The proposed features boost the RE performance significantly when these are combined with some linguistic features.
Type de document :
Chapitre d'ouvrage
Springer. Communications in Computer and Information Science, pp.31-47, 2018, Information Management and Big Data. Revised Selected Papers of SIMBig 2017
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https://hal.archives-ouvertes.fr/hal-01802577
Contributeur : Rashedur Rahman <>
Soumis le : mardi 29 mai 2018 - 14:42:48
Dernière modification le : mardi 20 novembre 2018 - 14:04:02

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  • HAL Id : hal-01802577, version 1

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LIMSI | UNIV-PARIS-SACLAY | IRT-SYSTEMX

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Rashedur Rahman, Brigitte Grau, Sophie Rosset. Impact of Entity Graphs on Extracting Semantic Relations. Springer. Communications in Computer and Information Science, pp.31-47, 2018, Information Management and Big Data. Revised Selected Papers of SIMBig 2017. 〈hal-01802577〉

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