Log-linear models of non-projective trees, k-best MST parsing and tree-ranking

Abstract 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 ...