Paper: Log-Linear Models of Non-Projective Trees $k$-best MST Parsing and Tree-Ranking

ACL ID D07-1102
Title Log-Linear Models of Non-Projective Trees $k$-best MST Parsing and Tree-Ranking
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

We present our system used in the CoNLL 2007 shared task on multilingual parsing. The system is composed of three compo- nents: a k-best maximum spanning tree (MST) parser, a tree labeler, and a reranker that orders the k-best labeled trees. We present two techniques for training the MST parser: tree-normalized and graph- normalized conditional training. The tree- based reranking model allows us to explic- itly model global syntactic phenomena. We describe the reranker features which include non-projective edge attributes. We provide an analysis of the errors made by our system and suggest changes to the models and fea- tures that might rectify the current system.