Paper: SFS-TUE: Compound Paraphrasing with a Language Model and Discriminative Reranking

ACL ID S13-2027
Title SFS-TUE: Compound Paraphrasing with a Language Model and Discriminative Reranking
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper presents an approach for gener- ating free paraphrases of compounds (task 4 at SemEval 2013) by decomposing the train- ing data into a collection of templates and fillers and recombining/scoring these based on a generative language model and discrimina- tive MaxEnt reranking. The system described in this paper achieved the highest score (with a very small margin) in the (default) isomorphic setting of the scorer, for which it was optimized, at a disadvantage to the non-isomorphic score.