Community graph and linguistic analysis to validate relationships for knowledge base population

Abstract : Relation extraction between entities from text plays an important role in information extraction and knowledge discovery related tasks. Relation extraction systems produce a large number of candidates where many of them are not correct. A relation validation method justifies a claimed relation based on the information provided by a system. In this paper, we propose some features by analyzing the community graphs of entities to account for some sort of world knowledge. The proposed features improve validation of relations significantly when they are combined with voting and some state-of-the-art linguistic features.
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Communication dans un congrès
4th International Symposium on Information Management and Big Data (SimBig 2017), Sep 2017, Lima, Peru. 2017
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Contributeur : Rashedur Rahman <>
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Dernière modification le : lundi 18 mars 2019 - 16:22:00
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  • HAL Id : hal-01617291, version 1

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Rashedur Rahman, Brigitte Grau, Sophie Rosset. Community graph and linguistic analysis to validate relationships for knowledge base population. 4th International Symposium on Information Management and Big Data (SimBig 2017), Sep 2017, Lima, Peru. 2017. 〈hal-01617291〉

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