@inproceedings{yoshikawa-etal-2019-detecting,
title = "Detecting Chemical Reactions in Patents",
author = "Yoshikawa, Hiyori and
Nguyen, Dat Quoc and
Zhai, Zenan and
Druckenbrodt, Christian and
Thorne, Camilo and
Akhondi, Saber A. and
Baldwin, Timothy and
Verspoor, Karin",
editor = "Mistica, Meladel and
Piccardi, Massimo and
MacKinlay, Andrew",
booktitle = "Proceedings of the 17th Annual Workshop of the Australasian Language Technology Association",
month = "4--6 " # dec,
year = "2019",
address = "Sydney, Australia",
publisher = "Australasian Language Technology Association",
url = "https://aclanthology.org/U19-1014",
pages = "100--110",
abstract = "Extracting chemical reactions from patents is a crucial task for chemists working on chemical exploration. In this paper we introduce the novel task of detecting the textual spans that describe or refer to chemical reactions within patents. We formulate this task as a paragraph-level sequence tagging problem, where the system is required to return a sequence of paragraphs which contain a description of a reaction. To address this new task, we construct an annotated dataset from an existing proprietary database of chemical reactions manually extracted from patents. We introduce several baseline methods for the task and evaluate them over our dataset. Through error analysis, we discuss what makes the task complex and challenging, and suggest possible directions for future research.",
}
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<abstract>Extracting chemical reactions from patents is a crucial task for chemists working on chemical exploration. In this paper we introduce the novel task of detecting the textual spans that describe or refer to chemical reactions within patents. We formulate this task as a paragraph-level sequence tagging problem, where the system is required to return a sequence of paragraphs which contain a description of a reaction. To address this new task, we construct an annotated dataset from an existing proprietary database of chemical reactions manually extracted from patents. We introduce several baseline methods for the task and evaluate them over our dataset. Through error analysis, we discuss what makes the task complex and challenging, and suggest possible directions for future research.</abstract>
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%0 Conference Proceedings
%T Detecting Chemical Reactions in Patents
%A Yoshikawa, Hiyori
%A Nguyen, Dat Quoc
%A Zhai, Zenan
%A Druckenbrodt, Christian
%A Thorne, Camilo
%A Akhondi, Saber A.
%A Baldwin, Timothy
%A Verspoor, Karin
%Y Mistica, Meladel
%Y Piccardi, Massimo
%Y MacKinlay, Andrew
%S Proceedings of the 17th Annual Workshop of the Australasian Language Technology Association
%D 2019
%8 4–6 dec
%I Australasian Language Technology Association
%C Sydney, Australia
%F yoshikawa-etal-2019-detecting
%X Extracting chemical reactions from patents is a crucial task for chemists working on chemical exploration. In this paper we introduce the novel task of detecting the textual spans that describe or refer to chemical reactions within patents. We formulate this task as a paragraph-level sequence tagging problem, where the system is required to return a sequence of paragraphs which contain a description of a reaction. To address this new task, we construct an annotated dataset from an existing proprietary database of chemical reactions manually extracted from patents. We introduce several baseline methods for the task and evaluate them over our dataset. Through error analysis, we discuss what makes the task complex and challenging, and suggest possible directions for future research.
%U https://aclanthology.org/U19-1014
%P 100-110
Markdown (Informal)
[Detecting Chemical Reactions in Patents](https://aclanthology.org/U19-1014) (Yoshikawa et al., ALTA 2019)
ACL
- Hiyori Yoshikawa, Dat Quoc Nguyen, Zenan Zhai, Christian Druckenbrodt, Camilo Thorne, Saber A. Akhondi, Timothy Baldwin, and Karin Verspoor. 2019. Detecting Chemical Reactions in Patents. In Proceedings of the 17th Annual Workshop of the Australasian Language Technology Association, pages 100–110, Sydney, Australia. Australasian Language Technology Association.