Summary of the paper

Title A Database of Attribution Relations
Authors Silvia Pareti
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.
Topics Corpus (creation, annotation, etc.), Person Identification, Discourse annotation, representation and processing
Full paper A Database of Attribution Relations
Bibtex @InProceedings{PARETI12.958,
  author = {Silvia Pareti},
  title = {A Database of Attribution Relations},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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