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    <abstract>We introduce an end-to-end system capable of named-entity detection, normalization and relation extraction for extracting information about bacteria and their habitats from biomedical literature. Our system is based on deep learning, CRF classifiers and vector space models. We train and evaluate the system on the BioNLP 2016 Shared Task Bacteria Biotope data. The official evaluation shows that the joint performance of our entity detection and relation extraction models outperforms the winning team of the Shared Task by 19pp on F1-score, establishing a new top score for the task. We also achieve state-of-the-art results in the normalization task. Our system is open source and freely available at https://github.com/TurkuNLP/BHE.</abstract>
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%0 Conference Proceedings
%T End-to-End System for Bacteria Habitat Extraction
%A Mehryary, Farrokh
%A Hakala, Kai
%A Kaewphan, Suwisa
%A Björne, Jari
%A Salakoski, Tapio
%A Ginter, Filip
%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 mehryary-etal-2017-end
%X We introduce an end-to-end system capable of named-entity detection, normalization and relation extraction for extracting information about bacteria and their habitats from biomedical literature. Our system is based on deep learning, CRF classifiers and vector space models. We train and evaluate the system on the BioNLP 2016 Shared Task Bacteria Biotope data. The official evaluation shows that the joint performance of our entity detection and relation extraction models outperforms the winning team of the Shared Task by 19pp on F1-score, establishing a new top score for the task. We also achieve state-of-the-art results in the normalization task. Our system is open source and freely available at https://github.com/TurkuNLP/BHE.
%R 10.18653/v1/W17-2310
%U https://aclanthology.org/W17-2310
%U https://doi.org/10.18653/v1/W17-2310
%P 80-90

Markdown (Informal)

[End-to-End System for Bacteria Habitat Extraction](https://aclanthology.org/W17-2310) (Mehryary et al., BioNLP 2017)

• End-to-End System for Bacteria Habitat Extraction (Mehryary et al., BioNLP 2017)

ACL

• Farrokh Mehryary, Kai Hakala, Suwisa Kaewphan, Jari Björne, Tapio Salakoski, and Filip Ginter. 2017. End-to-End System for Bacteria Habitat Extraction. In BioNLP 2017, pages 80–90, Vancouver, Canada,. Association for Computational Linguistics.