Paper: Weakly Supervised Supertagging with Grammar-Informed Initialization

ACL ID C08-1008
Title Weakly Supervised Supertagging with Grammar-Informed Initialization
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2008
Authors

Muchpreviousworkhasinvestigatedweak supervision with HMMs and tag dictionar- ies for part-of-speech tagging, but there have been no similar investigations for the harder problem of supertagging. Here, I show that weak supervision for supertag- ging does work, but that it is subject to severe performance degradation when the tag dictionary is highly ambiguous. I show that lexical category complexity and infor- mation about how supertags may combine syntactically can be used to initialize the transition distributions of a first-order Hid- den Markov Model for weakly supervised learning. This initialization proves more effective than starting with uniform tran- sitions, especially when the tag dictionary is highly ambiguous.