Paper: Language-Independent Discriminative Parsing of Temporal Expressions

ACL ID P13-1009
Title Language-Independent Discriminative Parsing of Temporal Expressions
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013

Temporal resolution systems are tradition- ally tuned to a particular language, re- quiring significant human effort to trans- late them to new languages. We present a language independent semantic parser for learning the interpretation of tempo- ral phrases given only a corpus of utter- ances and the times they reference. We make use of a latent parse that encodes a language-flexible representation of time, and extract rich features over both the parse and associated temporal semantics. The parameters of the model are learned using a weakly supervised bootstrapping approach, without the need for manually tuned parameters or any other language expertise. We achieve state-of-the-art ac- curacy on all languages in the TempEval- 2 temporal normalization task, reporting a 4% improvement in bot...