@inproceedings{d9ce0f0b5c05489da010fcf9857c2cf7,
title = "A Graph-based Method for Entity Linking",
abstract = "In this paper, we formalize the task of finding a knowledge base entry that a given named entity mention refers to, namely entity linking, by identifying the most “important” node among the graph nodes representing the candidate entries. With the aim of ranking these entities by their “importance”, we introduce three degree-based measures of graph connectivity. Experimental results on the TAC-KBP benchmark data sets show that our graph-based method performs comparably with the state-of-the-art methods. We also show that using the name phrase feature outperforms the commonly used bag-of-word feature for entity linking.",
author = "Yuhang Guo and Wanxiang Che and Ting Liu and Sheng Li",
note = "Publisher Copyright: {\textcopyright} 2011 AFNLP; 5th International Joint Conference on Natural Language Processing, IJCNLP 2011 ; Conference date: 08-11-2011 Through 13-11-2011",
year = "2011",
language = "English",
series = "IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing",
publisher = "Association for Computational Linguistics (ACL)",
pages = "1010--1018",
editor = "Haifeng Wang and David Yarowsky",
booktitle = "IJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing",
address = "United States",
}