Dependency Parser for Chinese Constituent Parsing ∗

This paper presents our work for participation in the 2010 CIPS-ParsEval shared task on Chinese syntactic constituent tree parsing. We use dependency parsers for this constituent parsing task based on a formal dependencyconstituent transformation method which converts dependency to constituent structures using a machine learning approach. A conditional random fields (CRF) tagger is adopted for head information recognition. Our experiments shows that acceptable parsing and head tagging results are obtained on our approaches.