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Cross-Domain Evaluation of Edge Detection for Biomedical Event Extraction

  • Fondazione the Microsoft Research – University of Trento Centre for Computational and Systems Biology, Italy

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

Biomedical event extraction is a crucial task in order to automatically extract information from the increasingly growing body of biomedical literature. Despite advances in the methods in recent years, most event extraction systems are still evaluated in-domain and on complete event structures only. This makes it hard to determine the performance of intermediate stages of the task, such as edge detection, across different corpora. Motivated by these limitations, we present the first cross-domain study of edge detection for biomedical event extraction. We analyze differences between five existing gold standard corpora, create a standardized benchmark corpus, and provide a strong baseline model for edge detection. Experiments show a large drop in performance when the baseline is applied on out-of-domain data, confirming the need for domain adaptation methods for the task. To encourage research efforts in this direction, we make both the data and the baseline available to the research community: https://www.cosbi.eu/cfx/9985.
OriginalsprogEngelsk
TitelProceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020)
Antal sider1982
ForlagEuropean Language Resources Association
Publikationsdatomaj 2020
Sider1975
StatusUdgivet - maj 2020
BegivenhedLREC 2022 - Palais du Pharo, Marseille, Frankrig
Varighed: 20 jun. 202225 jun. 2022
Konferencens nummer: 13
https://lrec2022.lrec-conf.org/en/

Konference

KonferenceLREC 2022
Nummer13
LokationPalais du Pharo
Land/OmrådeFrankrig
ByMarseille
Periode20/06/202225/06/2022
Internetadresse

Emneord

  • Biomedical event extraction
  • Edge detection
  • Cross-domain study
  • Standardized benchmark corpus
  • Domain adaptation methods

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