Overview of ChEMU 2020: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents

Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this paper, we provide an overview of the Cheminformatics Elsevier Melbourne University (ChEMU) evaluation lab 2020, part of the Conference and Labs of the Evaluation Forum 2020 (CLEF2020). The ChEMU evaluation lab focuses on information extraction over chemical reactions from patent texts. Using the ChEMU corpus of 1500 “snippets” (text segments) sampled from 170 patent documents and annotated by chemical experts, we defined two key information extraction tasks. Task 1 addresses chemical named entity recognition, the identification of chemical compounds and their specific roles in chemical reactions. Task 2 focuses on event extraction, the identification of reaction steps, relating the chemical compounds involved in a chemical reaction. Herein, we describe the resources created for these tasks and the evaluation methodology adopted. We also provide a brief summary of the participants of this lab and the results obtained across 46 runs from 11 teams, finding that several submissions achieve substantially better results than our baseline methods.
Original languageAmerican English
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Science and Business Media Deutschland GmbH
Pages237-254
Number of pages18
ISBN (Print)9783030582180
DOIs
StatePublished - 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12260 LNCS

Keywords

  • Chemical reactions
  • Event extraction
  • Information extraction
  • Named entity recognition
  • Patent text mining

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