TRIOS-TimeBank Corpus: Extended TimeBank Corpus with Help of Deep Understanding of Text

Naushad UzZaman, James Allen


Abstract
TimeBank (Pustejovsky et al, 2003a), a reference for TimeML (Pustejovsky et al, 2003b) compliant annotation, is widely used temporally annotated corpus in the community. It captures time expressions, events, and relations between events and event and temporal expression; but there is room for improvements in this hand-annotated widely used TimeBank corpus. This work is one such effort to extend the TimeBank corpus. Our first goal is to suggest missing TimeBank events and temporal expressions, i.e. events and temporal expressions that were missed by TimeBank annotators. Along with that this paper also suggests some additions to TimeML language by adding new event features (ontology type), some more SLINKs and also relations between events with their arguments, which we call RLINK (relation link). With our new suggestions we present the TRIOS-TimeBank corpus, an extended TimeBank corpus. We conclude by suggesting our future work to clean the TimeBank corpus even more and automatically generating larger temporally annotated corpus for the community.
Anthology ID:
L10-1109
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Mike Rosner, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/169_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Naushad UzZaman and James Allen. 2010. TRIOS-TimeBank Corpus: Extended TimeBank Corpus with Help of Deep Understanding of Text. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
Cite (Informal):
TRIOS-TimeBank Corpus: Extended TimeBank Corpus with Help of Deep Understanding of Text (UzZaman & Allen, LREC 2010)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/169_Paper.pdf