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2007. Modeling and Learning Vague Event Durations for Temporal Reasoning
| Venue: | In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI), Nectar Track |
| Citations: | 1 - 1 self |
BibTeX
@INPROCEEDINGS{Pan_2007.modeling,
author = {Feng Pan and Rutu Mulkar-mehta and Jerry R. Hobbs},
title = {2007. Modeling and Learning Vague Event Durations for Temporal Reasoning},
booktitle = {In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI), Nectar Track},
year = {},
pages = {1659--1662}
}
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Abstract
This paper reports on our recent work on modeling and automatically extracting vague, implicit event durations from text (Pan et al., 2006a, 2006b). It is a kind of commonsense knowledge that can have a substantial impact on temporal reasoning problems. We have also proposed a method of using normal distributions to model judgments that are intervals on a scale and measure their interannotator agreement; this should extend from time to other kinds of vague but substantive information in text and commonsense reasoning.
