Coreference based event extraction on biomedical text.
Transactions of the Japanese Society for Artificial Intelligence
This paper presents a new approach that exploits coreference information to extract event-argument (E-A) relations from biomedical documents. This approach has two advantages: (1) it can extract a large number of valuable E-A relations for document understanding based on the concept of salience in discourse; (2) it enables us to identify cross-sentence E-A using transitivity involving coreference relations. We propose two coreference-based models: a pipeline based on an Support Vector Machine (SVM) classifier, and a jointMarkov Logic Network (MLN). We show the effectiveness of these models on GENIA Event Corpus.
|Title:||Coreference based event extraction on biomedical text|
|Open access status:||An open access publication|
|Keywords:||Coreference resolution, Event extraction, Markov logic network|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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