Evaluating the word-expert approach for Named-Entity Disambiguation
Stanford University（斯坦福大学）；University of the Basque Country（巴斯克大学）
英文摘要：
Named Entity Disambiguation (NED) is the task of linking a named-entity mention to an instance in a knowledge-base, typically Wikipedia. This task is closely related to word-sense disambiguation (WSD), where the supervised word-expert approach has prevailed. In this work we present the results of the word-expert approach to NED, where one classifier is built for each target entity mention string. The resources necessary to build the system, a dictionary and a set of training instances, have been automatically derived from Wikipedia. We provide empirical evidence of the value of this approach, as well as a study of the differences between WSD and NED, including ambiguity and synonymy statistics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
