Paper: A Cascaded Machine Learning Approach to Interpreting Temporal Expressions

ACL ID N07-1053
Title A Cascaded Machine Learning Approach to Interpreting Temporal Expressions
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors

A new architecture for identifying and in- terpreting temporal expressions is intro- duced, in which the large set of com- plex hand-crafted rules standard in sys- tems for this task is replaced by a series of machine learned classifiers and a much smaller set of context-independent seman- tic composition rules. Experiments with the TERN 2004 data set demonstrate that overall system performance is comparable to the state-of-the-art, and that normaliza- tion performance is particularly good.