关键词: 命名实体消歧, 实体链接, 聚类

Abstract:

In order to eliminate the ambiguity of named entities in the documents, a named entity disambiguation algorithm combining entity linking and entity clustering is proposed, and the proposed algorithm combines two methods to compensate for the limitations of only using one of the methods. The proposed algorithm expands the mentions in the background document firstly, and generates candidates in the English Wikipedia knowledge base for expansions secondly, then extracts a variety of features to rank candidates, lastly uses clustering to disambiguate the mentions which has none candidates in the knowledge base. The experimental results show that, in the proposed algorithm, the F measure in KBP2011 data set is 0.746 and the F measure in KBP2012 data set is 0.670.

Key words: named entity disambiguation, entity linking, clustering