Named Entities (NEs) play an important role in many natural language and speech processing tasks. A resource that identifies relations between NEs could potentially be very useful. We present such automatically generated knowledge resource from Wikipedia, Named Entity Network (NE-NET), that provides a list of related Named Entities (NEs) and the degree of relation for any given NE. Unlike some manually built knowledge resource, NE-NET has a wide coverage consisting of 1.5 million NEs represented as nodes of a graph with 6.5 million arcs relating them. NE-NET also provides the ranks of the related NEs using a simple ranking function that we propose. In this paper, we present NE-NET and our experiments showing how NE-NET can be used to improve the retrieval of spoken (Broadcast News) and text documents.
Cite as: Maskey, S., Dakka, W. (2009) Named entity network based on wikipedia. Proc. Interspeech 2009, 1515-1518, doi: 10.21437/Interspeech.2009-460
@inproceedings{maskey09_interspeech,
author={Sameer Maskey and Wisam Dakka},
title={{Named entity network based on wikipedia}},
year=2009,
booktitle={Proc. Interspeech 2009},
pages={1515--1518},
doi={10.21437/Interspeech.2009-460}
}