Log-Linear Models of Non-Projective Trees, $k$-best MST Parsing and Tree-Ranking
Keith Hall, Jiří Havelka, David A. Smith · 2007
We present our system used in the CoNLL 2007 shared task on multilingual parsing. The system is composed of three components: 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 graphnormalized conditional training. The treebased reranking model allows us to explicitly 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 features that might rectify the current system.