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Extracting Complex Information from Natural Language Text: A Survey

Abstract : Information Extraction is the art of extracting structured information from natural language text, and it has come a long way in recent years. Many systems focus on binary relationships between two entities-a subject and an object. However, most natural language text contains complex information such as beliefs, causality, anteriority, or relationships that span several sentences. In this paper, we survey existing approaches at this frontier, and outline promising directions of future work.
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Contributor : Fabian Suchanek Connect in order to contact the contributor
Submitted on : Thursday, January 7, 2021 - 6:33:19 PM
Last modification on : Thursday, October 27, 2022 - 1:45:02 PM
Long-term archiving on: : Thursday, April 8, 2021 - 7:53:25 PM


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  • HAL Id : hal-03102913, version 1



Emna Mechket, Fabian Suchanek. Extracting Complex Information from Natural Language Text: A Survey. Workshop on Semantic and knowledge graph advances for journalism, 2020. ⟨hal-03102913⟩



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