---
title: "Improving Heuristic-Based Temporal Analysis of Narratives with Aspect Determination"
authors:
  - "Fei Song"
  - "Robin Cohen"
doi: ""
url: "https://ijcai.org/proceedings/1995/172"
pdf: "https://ijcai.org/proceedings/1995/0172.pdf"
venue: "Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence"
year: 1995
pages: "1338-1344"
track: "Natural Language"
keywords:
---

# Improving Heuristic-Based Temporal Analysis of Narratives with Aspect Determination

Fei Song, Robin Cohen

*Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence*, pages 1338-1344.

## 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.