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Scaling up Biomedical Event Extraction to the Entire PubMed

Jari Björne, Filip Ginter, Sampo Pyysalo, Jun'ichi Tsujii, Tapio Salakoski, Scaling up Biomedical Event Extraction to the Entire PubMed. In: Proceedings of the 2010 Workshop on Biomedical Natural Language Processing, pp. 28-36, 2010.

Abstract:

We present the first full-scale event extraction
experiment covering the titles and abstracts
of all PubMed citations. Extraction
is performed using a pipeline composed
of state-of-the-art methods: the BANNER
named entity recognizer, the McClosky-
Charniak domain-adapted parser, and the
Turku Event Extraction System. We analyze
the statistical properties of the resulting
dataset and present evaluations of
the core event extraction as well as negation
and speculation detection components
of the system. Further, we study in detail
the set of extracted events relevant
to the apoptosis pathway to gain insight
into the biological relevance of the result.
The dataset, consisting of 19.2 million occurrences
of 4.5 million unique events,
is freely available for use in research at
http://bionlp.utu.fi/.

BibTeX entry:

@INPROCEEDINGS{inpBjGiPyTsSa10a,
  title = {Scaling up Biomedical Event Extraction to the Entire PubMed},
  booktitle = {Proceedings of the 2010 Workshop on Biomedical Natural Language Processing},
  author = {Björne, Jari and Ginter, Filip and Pyysalo, Sampo and Tsujii, Jun'ichi and Salakoski, Tapio},
  pages = {pp. 28-36},
  year = {2010},
}

Belongs to TUCS Research Unit(s): Turku BioNLP Group

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