CLC number: TP391.1
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2017-01-20
Cited: 0
Clicked: 6860
Hui Chen, Bao-gang Wei, Yi-ming Li, Yong-huai Liu, Wen-hao Zhu. An easy-to-use evaluation framework for benchmarking entity recognition and disambiguation systems[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(2): 195-205.
@article{title="An easy-to-use evaluation framework for benchmarking entity recognition and disambiguation systems",
author="Hui Chen, Bao-gang Wei, Yi-ming Li, Yong-huai Liu, Wen-hao Zhu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="2",
pages="195-205",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500473"
}
%0 Journal Article
%T An easy-to-use evaluation framework for benchmarking entity recognition and disambiguation systems
%A Hui Chen
%A Bao-gang Wei
%A Yi-ming Li
%A Yong-huai Liu
%A Wen-hao Zhu
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 2
%P 195-205
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500473
TY - JOUR
T1 - An easy-to-use evaluation framework for benchmarking entity recognition and disambiguation systems
A1 - Hui Chen
A1 - Bao-gang Wei
A1 - Yi-ming Li
A1 - Yong-huai Liu
A1 - Wen-hao Zhu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 2
SP - 195
EP - 205
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500473
Abstract: entity recognition and disambiguation (ERD) is a crucial technique for knowledge base population and information extraction. In recent years, numerous papers have been published on this subject, and various ERD systems have been developed. However, there are still some confusions over the ERD field for a fair and complete comparison of these systems. Therefore, it is of emerging interest to develop a unified evaluation framework. In this paper, we present an easy-to-use evaluation framework (EUEF), which aims at facilitating the evaluation process and giving a fair comparison of ERD systems. EUEF is well designed and released to the public as an open source, and thus could be easily extended with novel ERD systems, datasets, and evaluation metrics. It is easy to discover the advantages and disadvantages of a specific ERD system and its components based on EUEF. We perform a comparison of several popular and publicly available ERD systems by using EUEF, and draw some interesting conclusions after a detailed analysis.
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