Abstract

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.

Date

March 19, 2026

Authors

Xuezhe Ma, Xiaotian Zhang, Hai Zhao, Bao-Liang Lu

Conference

CIPS-SIGHAN Joint Conference on Chinese Language Processing