A Database of Attribution Relations

Silvia Pareti

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Abstract
The importance of attribution is becoming evident due to its relevance in particular for Opinion Analysis and Information Extraction applications. Attribution would allow to identify different perspectives on a given topic or retrieve the statements of a specific source of interest, but also to select more relevant and reliable information. However, the scarce and partial resources available to date to conduct attribution studies have determined that only a portion of attribution structures has been identified and addressed. This paper presents the collection and further annotation of a database of over 9800 attributions relations from the Penn Discourse TreeBank (PDTB). The aim is to build a large and complete resource that fills a key gap in the field and enables the training and testing of robust attribution extraction systems.
Anthology ID:
L12-1571
Volume:
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
Month:
May
Year:
2012
Address:
Istanbul, Turkey
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Mehmet Uğur Doğan, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3213–3217
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2012/pdf/958_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Silvia Pareti. 2012. A Database of Attribution Relations. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 3213–3217, Istanbul, Turkey. European Language Resources Association (ELRA).
Cite (Informal):
A Database of Attribution Relations (Pareti, LREC 2012)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2012/pdf/958_Paper.pdf