SFS-TUE: Compound Paraphrasing with a Language Model and Discriminative Reranking
Yannick Versley · Joint Conference on Lexical and Computational Semantics · 2013
This paper presents an approach for generating free paraphrases of compounds (task 4 at SemEval 2013) by decomposing the training data into a collection of templates and fillers and recombining/scoring these based on a generative language model and discriminative 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.