Making adjustments to event annotations for improved biological event extraction.

Journal: Journal of biomedical semantics
Published Date:

Abstract

BACKGROUND: Current state-of-the-art approaches to biological event extraction train statistical models in a supervised manner on corpora annotated with event triggers and event-argument relations. Inspecting such corpora, we observe that there is ambiguity in the span of event triggers (e.g., "transcriptional activity" vs. 'transcriptional'), leading to inconsistencies across event trigger annotations. Such inconsistencies make it quite likely that similar phrases are annotated with different spans of event triggers, suggesting the possibility that a statistical learning algorithm misses an opportunity for generalizing from such event triggers.

Authors

  • Seung-Cheol Baek
    Department of Computer Science, KAIST, 291 Daehak-ro, Daejeon, Republic of Korea. scbaek@nlp.kaist.ac.kr.
  • Jong C Park
    Department of Computer Science, KAIST, 291 Daehak-ro, Daejeon, Republic of Korea.