Improving Heuristic-Based Temporal Analysis of Narratives with Aspect Determination

Abstract

In previous work we presented an algorithm for tense interpretation which employs a temporal focus to determine the intended temporal relations between the states and events mentioned in a narrative In this paper, we propose a new two-phased classification scheme for aspect Each situation described in an utterance is first classified as static (state) or dynamic (event) and if dynamic as telic (event with a culmination point) or atelic (event without a culmination point) Then, independent of the class the view of the situation is identified either as a point or as an interval We then demonstrate how the determination of aspect can be integrated into our tense interpretation algorithm to produce a richer analysis of temporal relations Our classification for aspect is more detailed than most of the existing schemes allowing us to extract the interval relations between situations and cover a wide range of English narratives.

Cite

Text

Song and Cohen. "Improving Heuristic-Based Temporal Analysis of Narratives with Aspect Determination." International Joint Conference on Artificial Intelligence, 1995.

Markdown

[Song and Cohen. "Improving Heuristic-Based Temporal Analysis of Narratives with Aspect Determination." International Joint Conference on Artificial Intelligence, 1995.](https://mlanthology.org/ijcai/1995/song1995ijcai-improving/)

BibTeX

@inproceedings{song1995ijcai-improving,
  title     = {{Improving Heuristic-Based Temporal Analysis of Narratives with Aspect Determination}},
  author    = {Song, Fei and Cohen, Robin},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1995},
  pages     = {1338-1345},
  url       = {https://mlanthology.org/ijcai/1995/song1995ijcai-improving/}
}