@inproceedings{a9fb0a859ac141b780e2e20dbd211101,
title = "Infusion of labeled data into distant supervision for relation extraction",
abstract = "Distant supervision usually utilizes only unlabeled data and existing knowledge bases to learn relation extraction models. However, in some cases a small amount of human labeled data is available. In this paper, we demonstrate how a state-of-theart multi-instance multi-label model can be modified to make use of these reliable sentence-level labels in addition to the relation-level distant supervision from a database. Experiments show that our approach achieves a statistically significant increase of 13.5% in F-score and 37% in area under the precision recall curve.",
author = "Maria Pershina and Bonan Min and Wei Xu and Ralph Grishman",
year = "2014",
doi = "10.3115/v1/p14-2119",
language = "English (US)",
isbn = "9781937284732",
series = "52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "732--738",
booktitle = "Long Papers",
note = "52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 ; Conference date: 22-06-2014 Through 27-06-2014",
}