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Gmane
From: Paul Thompson <Paul.Thompson <at> manchester.ac.uk>
Subject: New paper on improving event extraction using coreference resolution and domain adaptation
Newsgroups: gmane.science.linguistics.corpora
Date: Wednesday 2nd May 2012 13:55:09 UTC (over 4 years ago)
Boosting automatic event extraction from the literature using domain
adaptation and coreference resolution

Makoto Miwa, Paul Thompson and Sophia Ananiadou

Bioinformatics 2012; doi: 10.1093/bioinformatics/bts237

http://bioinformatics.oxfordjournals.org/cgi/content/abstract/bts237?
ijkey=oTLQoB9dzQDyjzV&keytype=ref<http://bioinformatics.oxfordjournals.org/cgi/content/abstract/bts237?ijkey=oTLQoB9dzQDyjzV&keytype=ref>

Abstract
======

Motivation:
In recent years, several biomedical event extraction (EE) systems have been
developed. However, the nature of the annotated training corpora, as well
as the training process itself, can limit the performance levels of the
trained EE systems. In particular, most event-annotated corpora do not deal
adequately with coreference. This impacts on the trained systems’ ability
to recognise biomedical entities, thus affecting their performance in
extracting events accurately. Additionally, the fact that most EE systems
are trained on a single annotated corpus further restricts their coverage.

Results:
We have enhanced our existing EE system, EventMine, in two ways. Firstly,
we developed a new coreference resolution (CR) system and integrated it
with EventMine. The standalone performance of our CR system in resolving
anaphoric references to proteins is considerably higher than the best
ranked system in the COREF subtask of the BioNLP’11 Shared Task.
Secondly, the improved EventMine incorporates domain adaptation (DA)
methods, which extend EE coverage by allowing several different annotated
corpora to be used during training. Combined with a novel set of methods to
increase the generality and efficiency of EventMine, the integration of
both CR and DA have resulted in significant improvements in EE, ranging
between 0.5% and 3.4% F-Score. The enhanced EventMine outperforms the
highest ranked systems from the BioNLP’09 shared task, and from the GENIA
and Infectious Diseases subtasks of the BioNLP’11 shared task.

Availability:
The improved version of EventMine, incorporating the CR system and DA
methods, is available at: <http://www.nactem.ac.uk/EventMine/>
http://www.nactem.ac.uk/EventMine/.




--------

Paul Thompson
Research Associate
School of Computer Science
National Centre for Text Mining
Manchester Interdisciplinary Biocentre
University of Manchester
131 Princess Street
Manchester
M1 7DN
UK
Tel: 0161 306 3091
http://personalpages.manchester.ac.uk/staff/Paul.Thompson/
 
CD: 4ms