关键词: 人名消歧, 信息抽取, 相似度, 层次聚类

Abstract: Cross-document entity disambiguation is the problem of identifying whether mentions from different documents refer to the same or distinct entities. This paper describes a Chinese information extraction system which involves both document-level IE and corpus-level IE, a pipeline and multi-level modular approach to name entity and Entity Profile extraction. It introduces novel features based on document-level entity profiles and study on the influence of feature selection, parameter selection, parameter validation and analysis on results. Disambiguation is performed based on agglomerative hierarchical clustering using Hadoop. Experiments show that F-measure of training set is 91.33% and testing set is 88.73%, using the whole network news corpus dataset from Harbin Institute of Technology.

Key words: entity disambiguation, information extraction, similarity, hierarchical clustering