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Tracking Point of View in Narrative

Paper · 1994 · Janyce M. Wiebe

Summary

Third-person fiction mixes objective narration with passages that convey what a character thinks, perceives or feels. Wiebe frames this as the task of tracking psychological point of view. For each sentence, a reader must decide whether it is objective or subjective, and if subjective, which character it belongs to. This is hard because explicit cues such as "Dennys thought" are rare, so the answer usually depends on context. Wiebe studied published novels and short stories to find regular patterns in how authors shift and maintain point of view. She then turned these patterns into an implemented algorithm. It takes clause-level input, including the type of state of affairs described, and labels each sentence as objective or as subjective for a particular character. Preliminary tests on passages from novels showed low error rates. Getting point of view right matters for separating story facts from character beliefs, for attributing attitudes to the correct source, for plan recognition and for interpreting discourse relations.

Key points

  • The algorithm builds on Banfield's notions of subjective sentences and subjective elements. Its main targets are represented thoughts and perceptions and private-state reports. It also treats private-state actions such as sighing or looking, but excludes represented speech.
  • Each sentence is assigned a point-of-view operation: continuation, resumption, initiation or objective. The subjective character is identified for subjective sentences.
  • In the Lonesome Dove evaluation, the algorithm made 20 primary errors on 271 truly subjective sentences. Of these, 13 were labeled objective and 7 were assigned to the wrong character.
  • On 450 input items from The Magic of the Glits, there were 34 primary errors (8%) and 21 secondary errors (5%). Most stemmed from minor subjective contexts of a secondary character, Lynette.
  • Treating private-state actions as private states only after a "significant" earlier subjective context would cut these errors to 22 primary (5%) and 7 secondary (2%). This heuristic was proposed but not yet incorporated into the algorithm.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

Cite

Cite as Janyce M. Wiebe. 1994. Tracking Point of View in Narrative. Computational Linguistics.

The paper itself, not this page. BibTeX from the library's record of the work.

@article{wiebe1994tracking,
  title = {{Tracking Point of View in Narrative}},
  author = {Janyce M. Wiebe},
  journal = {Computational Linguistics},
  year = {1994},
  doi = {10.5555/972525.972529},
  url = {https://doi.org/10.5555/972525.972529}
}

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