Summary of the paper

Title Towards Automatic Detection of Narrative Structure
Authors Jessica Ouyang and Kathy Mckeown
Abstract We present novel computational experiments using William Labov's theory of narrative analysis. We describe his six elements of narrative structure and construct a new corpus based on his most recent work on narrative. Using this corpus, we explore the correspondence between Labov’s elements of narrative structure and the implicit discourse relations of the Penn Discourse Treebank, and we construct a mapping between the elements of narrative structure and the discourse relation classes of the PDTB. We present first experiments on detecting Complicating Actions, the most common of the elements of narrative structure, achieving an f-score of 71.55. We compare the contributions of features derived from narrative analysis, such as the length of clauses and the tenses of main verbs, with those of features drawn from work on detecting implicit discourse relations. Finally, we suggest directions for future research on narrative structure, such as applications in assessing text quality and in narrative generation.
Topics Discourse Annotation, Representation and Processing, Tools, Systems, Applications
Full paper Towards Automatic Detection of Narrative Structure
Bibtex @InProceedings{OUYANG14.1154,
  author = {Jessica Ouyang and Kathy Mckeown},
  title = {Towards Automatic Detection of Narrative Structure},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
Powered by ELDA © 2014 ELDA/ELRA