Towards Automatic Detection of Narrative Structure

Jessica Ouyang, 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.
Anthology ID:
L14-1108
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
4624–4631
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1154_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Jessica Ouyang and Kathy McKeown. 2014. Towards Automatic Detection of Narrative Structure. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4624–4631, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Towards Automatic Detection of Narrative Structure (Ouyang & McKeown, LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1154_Paper.pdf
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