Summary of the paper

Title Improving the Annotation of Sentence Specificity
Authors Junyi Jessy Li, Bridget O'Daniel, Yi Wu, Wenli Zhao and Ani Nenkova
Abstract We introduce improved guidelines for annotation of sentence specificity, addressing the issues encountered in prior work. Our annotation provides judgements of sentences in context. Rather than binary judgements, we introduce a specificity scale which accommodates nuanced judgements. Our augmented annotation procedure also allows us to define where in the discourse context the lack of specificity can be resolved. In addition, the cause of the underspecification is annotated in the form of free text questions. We present results from a pilot annotation with this new scheme and demonstrate good inter-annotator agreement. We found that the lack of specificity distributes evenly among immediate prior context, long distance prior context and no prior context. We find that missing details that are not resolved in the the prior context are more likely to trigger questions about the reason behind events, ``why'' and ``how''. Our data is accessible at http://www.cis.upenn.edu/~nlp/corpora/lrec16spec.html
Topics Discourse Annotation, Representation and Processing, Corpus (Creation, Annotation, etc.), Other
Full paper Improving the Annotation of Sentence Specificity
Bibtex @InProceedings{LI16.930,
  author = {Junyi Jessy Li and Bridget O'Daniel and Yi Wu and Wenli Zhao and Ani Nenkova},
  title = {Improving the Annotation of Sentence Specificity},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portorož, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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