Paper: Discriminative Parse Reranking for Chinese with Homogeneous and Heterogeneous Annotations

ACL ID W10-4144
Title Discriminative Parse Reranking for Chinese with Homogeneous and Heterogeneous Annotations
Venue Joint Conference on Chinese Language Processing
Session Main Conference
Year 2010
Authors

Discriminative parse reranking has been shown to be an effective technique to im- prove the generative parsing models. In this paper, we present a series of exper- iments on parsing the Tsinghua Chinese Treebank with hierarchically split-merge grammars and reranked with a perceptron- based discriminative model. In addition to the homogeneous annotation on TCT, we also incorporate the PCTB-based parsing result as heterogeneous annotation into the reranking feature model. The rerank- ing model achieved 1.12% absolute im- provement on F1 over the Berkeley parser on a development set. The head labels in Task 2.1 are annotated with a sequence labeling model. The system achieved 80.32 (B+C+H F1) in CIPS-SIGHAN- 2010 Task 2.1 (Open Track) and 76.11 (Overall F1) in Task 2.2 (Open Track)1.