Paper: Parsing Time: Learning to Interpret Time Expressions

ACL ID N12-1049
Title Parsing Time: Learning to Interpret Time Expressions
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012

We present a probabilistic approach for learn- ing to interpret temporal phrases given only a corpus of utterances and the times they ref- erence. While most approaches to the task have used regular expressions and similar lin- ear pattern interpretation rules, the possibil- ity of phrasal embedding and modification in time expressions motivates our use of a com- positional grammar of time expressions. This grammar is used to construct a latent parse which evaluates to the time the phrase would represent, as a logical parse might evaluate to a concrete entity. In this way, we can employ a loosely supervised EM-style bootstrapping approach to learn these latent parses while capturing both syntactic uncertainty and prag- matic ambiguity in a probabilistic framework. We achieve an accuracy of...