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    <abstract>Relation extraction methods are essential for creating robust text mining tools to help researchers find useful knowledge in the vast published literature. Easy-to-use and generalizable methods are needed to encourage an ecosystem in which researchers can easily use shared resources and build upon each others’ methods. We present the Kindred Python package for relation extraction. It builds upon methods from the most successful tools in the recent BioNLP Shared Task to predict high-quality predictions with low computational cost. It also integrates with PubAnnotation, PubTator, and BioNLP Shared Task data in order to allow easy development and application of relation extraction models.</abstract>
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%0 Conference Proceedings
%T Painless Relation Extraction with Kindred
%A Lever, Jake
%A Jones, Steven
%Y Cohen, Kevin Bretonnel
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S BioNLP 2017
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada,
%F lever-jones-2017-painless
%X Relation extraction methods are essential for creating robust text mining tools to help researchers find useful knowledge in the vast published literature. Easy-to-use and generalizable methods are needed to encourage an ecosystem in which researchers can easily use shared resources and build upon each others’ methods. We present the Kindred Python package for relation extraction. It builds upon methods from the most successful tools in the recent BioNLP Shared Task to predict high-quality predictions with low computational cost. It also integrates with PubAnnotation, PubTator, and BioNLP Shared Task data in order to allow easy development and application of relation extraction models.
%R 10.18653/v1/W17-2322
%U https://aclanthology.org/W17-2322
%U https://doi.org/10.18653/v1/W17-2322
%P 176-183

Markdown (Informal)

[Painless Relation Extraction with Kindred](https://aclanthology.org/W17-2322) (Lever & Jones, BioNLP 2017)

• Painless Relation Extraction with Kindred (Lever & Jones, BioNLP 2017)

ACL

• Jake Lever and Steven Jones. 2017. Painless Relation Extraction with Kindred. In BioNLP 2017, pages 176–183, Vancouver, Canada,. Association for Computational Linguistics.