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Cardinal Virtues: Extracting Relation Cardinalities from Text
Conference proceeding   Peer reviewed

Cardinal Virtues: Extracting Relation Cardinalities from Text

Paramita Mirza, Simon Razniewski, Fariz Darari and Gerhard Weikum
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Vol.2, pp.347-351
2
Annual Meeting of the Association for Computational Linguistics (ACL) (Vancouver, 30/07/2017–04/08/2017)
2017
Handle:
https://hdl.handle.net/10863/53220

Abstract

Cardinalities Conditional random field Evaluation results Perfect recalls
Information extraction (IE) from text has largely focused on relations between individual entities, such as who has won which award. However, some facts are never fully mentioned, and no IE method has perfect recall. Thus, it is beneficial to also tap contents about the cardinalities of these relations, for example, how many awards someone has won. We introduce this novel problem of extracting cardinalities and discuss specific challenges that set it apart from standard IE. We present a distant supervision method using conditional random fields. A preliminary evaluation results in precision between 3% and 55%, depending on the difficulty of relations.
url
https://aclanthology.org/P17-2055/View
url
https://dx.doi.org/10.18653/v1/P17-2055View

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