Modeling and learning vague event durations for temporal reasoning
Feng Pan, Rutu Mulkar-Mehta, Jerry R. Hobbs · 2007
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 inter-annotator agreement; this should extend from time to other kinds of vague but substantive information in text and commonsense reasoning.