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The GENIA Corpus: Annotation Levels and Applications

  • Paul Thompson
  • Sophia AnaniadouEmail author
  • Jun’ichi Tsujii
Chapter

Abstract

The GENIA project was created with the aim of supporting the development and evaluation of information extraction and text mining systems in molecular biology. One of the main outcomes of the project has been the GENIA corpus, consisting of 1,999 MEDLINE abstracts. Over the course of several years, the corpus has been continually enriched with various levels of syntactic, semantic and discourse-level annotation, making it suitable for training various types of systems. The GENIA corpus has been widely used by the NLP community for the development of several semantic search systems, and motivated the establishment of the BioNLP shared task series of challenges. These challenges have been instrumental in pushing forward research into event extraction systems in the biomedical domain, and have also resulted in the development of a range of associated corpora in various biomedical sub-domains, annotated according to the GENIA guidelines.

Keywords

Syntactic annotation Semantic annotation Information extraction Biomedical event extraction Biomedical text mining Semantic search 

Notes

Acknowledgements

This work has been supported by the BBSRC-funded EMPATHY project (Grant No. BB/M006891/1) and by the EPSRC and MRC-funded MMPathIC project (Grant No. MR/N00583X/1).

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© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Paul Thompson
    • 1
  • Sophia Ananiadou
    • 1
    Email author
  • Jun’ichi Tsujii
    • 1
    • 2
  1. 1.National Centre for Text Mining, School of Computer ScienceUniversity of ManchesterManchesterUK
  2. 2.Artificial Intelligence Research CenterNational Institute of Advanced Industrial Science and TechnologyTokyoJapan

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