Detecting Chemical Reactions in Patents

Hiyori Yoshikawa, Dat Quoc Nguyen, Zenan Zhai, Christian Druckenbrodt, Camilo Thorne, Saber A. Akhondi, Timothy Baldwin, Karin Verspoor

Research output: Contribution to journalConference articlepeer-review

11 Scopus citations

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 that 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.

Original languageEnglish
JournalProceedings of the Australasian Language Technology Workshop
Volume17
StatePublished - 2019
Externally publishedYes
Event17th Annual Workshop of the Australasian Language Technology Association, ALTA 2019 - Sydney, Australia
Duration: Dec 4 2019Dec 6 2019

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