- Introduction
- Important dates
- Task definitions
- Download
- Results
- Paper submission
- Organisers
In Natural Language Processing (NLP) - in particular, in Information Extraction (IE) - many applications aim at extracting factual information from text. In order to distinguish facts from unreliable or uncertain information, linguistic devices such as hedges (indicating that authors do not or cannot back up their opinions/statements with facts) have to be identified. Applications should handle detected speculative parts in a different manner.
Hedge detection has received considerable interest recently in the biomedical NLP community, including research papers addressing the detection of hedge devices in biomedical texts, and some recent work on detecting the in-sentence scope of hedge cues in text. Exploiting the hedge scope annotated BioScope corpus and publicly available Wikipedia weasel annotations, the goals of the Shared Task are
Task 1: learning to detect sentences containing uncertainty and
Task 2: learning to resolve the in-sentence scope of hedge cues.
The shared task will be part of the CoNLL conference to be held in conjunction with ACL 2010 in Uppsala, Sweden, July 15-16, 2010.
For more information please visit the FAQ site or contact: conll2010st(AT)inf(DOT)u-szeged(DOT)hu.
Veronika Vincze, György Szarvas, Richárd Farkas, György Mora, and János Csirik: The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes. BMC Bioinformatics, 9(Suppl 11):S9, 2008.
Viola Ganter and Michael Strube: Finding hedges by chasing weasels: Hedge detection using wikipedia tags and shallow linguistic features. In Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pages 173-176, Suntec, Singapore, August 2009. Association for Computational Linguistics.
Roser Morante and Walter Daelemans: Learning the scope of hedge cues in biomedical texts. In Proceedings of the BioNLP 2009 Workshop, pages 28-36, Boulder, Colorado, June 2009. Association for Computational Linguistics.
The important dates for the shared task are as follows (please note that the dates are tentative for now):
The CoNLL-2010 Shared Task is organised by the Human Language Technology Group, University of Szeged.
Organising team:
Richárd Farkas, Human Language Technology Group, University of Szeged
Veronika Vincze, Human Language Technology Group, University of Szeged
György Szarvas, Ubiquitous Knowledge Processing Lab, Technische Universitaat Darmstadt
György Móra, Human Language Technology Group, University of Szeged
János Csirik, Research Group of Artificial Intelligence, Hungarian Academy of Sciences