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        <title>Open-Domain Event Detection using Distant Supervision</title>
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            <title>Proceedings of the 27th International Conference on Computational Linguistics</title>
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            <namePart type="given">Emily</namePart>
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            <namePart type="family">Bender</namePart>
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    <abstract>This paper introduces open-domain event detection, a new event detection paradigm to address issues of prior work on restricted domains and event annotation. The goal is to detect all kinds of events regardless of domains. Given the absence of training data, we propose a distant supervision method that is able to generate high-quality training data. Using a manually annotated event corpus as gold standard, our experiments show that despite no direct supervision, the model outperforms supervised models. This result indicates that the distant supervision enables robust event detection in various domains, while obviating the need for human annotation of events.</abstract>
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%0 Conference Proceedings
%T Open-Domain Event Detection using Distant Supervision
%A Araki, Jun
%A Mitamura, Teruko
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F araki-mitamura-2018-open
%X This paper introduces open-domain event detection, a new event detection paradigm to address issues of prior work on restricted domains and event annotation. The goal is to detect all kinds of events regardless of domains. Given the absence of training data, we propose a distant supervision method that is able to generate high-quality training data. Using a manually annotated event corpus as gold standard, our experiments show that despite no direct supervision, the model outperforms supervised models. This result indicates that the distant supervision enables robust event detection in various domains, while obviating the need for human annotation of events.
%U https://aclanthology.org/C18-1075
%P 878-891

Markdown (Informal)

[Open-Domain Event Detection using Distant Supervision](https://aclanthology.org/C18-1075) (Araki & Mitamura, COLING 2018)

• Open-Domain Event Detection using Distant Supervision (Araki & Mitamura, COLING 2018)

ACL

• Jun Araki and Teruko Mitamura. 2018. Open-Domain Event Detection using Distant Supervision. In Proceedings of the 27th International Conference on Computational Linguistics, pages 878–891, Santa Fe, New Mexico, USA. Association for Computational Linguistics.