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|Title:||A multi-resolution framework for Information Extraction from free text||Authors:||Maslennikov, M.
|Issue Date:||2007||Citation:||Maslennikov, M.,Chua, T.-S. (2007). A multi-resolution framework for Information Extraction from free text. ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics : 592-599. ScholarBank@NUS Repository.||Abstract:||Extraction of relations between entities is an important part of Information Extraction on free text. Previous methods are mostly based on statistical correlation and dependency relations between entities. This paper re-examines the problem at the multiresolution layers of phrase, clause and sentence using dependency and discourse relations. Our multi-resolution framework ARE (Anchor and Relation) uses clausal relations in 2 ways: 1) to filter noisy dependency paths; and 2) to increase reliability of dependency path extraction. The resulting system outperforms the previous approaches by 3%, 7%, 4% on MUC4, MUC6 and ACE RDC domains respectively. © 2007 Association for Computational Linguistics.||Source Title:||ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics||URI:||http://scholarbank.nus.edu.sg/handle/10635/42219||ISBN:||9781932432862|
|Appears in Collections:||Staff Publications|
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