A Reranking Method for Syntactic Parsing with Heterogeneous Treebanks

摘要：

In the field of natural language processing (NLP), there often exist multiple corpora with different annotation standards for the same task. In this paper, we take syntactic parsing as a case study and propose a reranking method which is able to make direct use of disparate treebanks simultaneously without using techniques such as treebank conversion. The method proceeds in three steps: 1) build parsers on individual treebanks; 2) use parsers independently to generate n-best lists for each sentence in test set; 3) rerank individual n-best lists which correspond to the same sentence by using consensus information exchanged among these n-best lists. Experimental results on two open Chinese treebanks show that our method significantly outperforms the baseline system by 0.84％ and 0.53％ respectively.

关键词： Syntactic parsing reranking heterogeneous treebanks

作者: Haibo DING Muhua ZHU Jingbo ZHU

作者单位: Natural Language Processing　Laboratory, Northeastern University,Shenyang, Liaoning, China

会议类型: 国际会议

会议名称: The 6th International Conference on Natural Language Processing and Knowledge Engineering(第六届IEEE自然语言处理与知识工程国际会议 NLP-KE 2010)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2010-08-21（万方平台首次上网日期，不代表论文的发表时间）