Relation Extraction Evaluation
Relation Extraction Evaluation is a scholarly assessment framework that systematically measures the accuracy, reliability, and effectiveness of relation extraction models or systems in identifying semantic relationships between entities within unstructured text, distinguishing it from general natural language processing evaluation by its specific focus on relational data extraction performance.
236
Publications
15.1K
Citations
683
Authors
247
Institutions
Publications per year
2017–2026
101
Parents
236
Eugene Agichtein, Luis Gravano · 2000 · 1.2K citations
Exploring various knowledge in relation extraction
Open Language Learning for Information Extraction
Michael Schmitz, Stephen Soderland, Robert Bart et al. · 2012 · 717 citations
RelEx—Relation extraction using dependency parse trees
Katrin Fundel, Robert Küffner, Ralf Zimmer · Bioinformatics · 2006 · 569 citations · Full text
1–5 of 236
683
5
h-index
5
h-index
5
h-index
5
h-index
4
h-index
1–5 of 683
247
University of Washington
Seattle, United States
6 h-index
18 publications
3.3K citations
Tsinghua University
Beijing, China
5 h-index
28 publications
5.2K citations
Fondazione Bruno Kessler
Trento, Italy
5 h-index
8 publications
681 citations
New York University
New York, United States
5 h-index
9 publications
970 citations
Columbia University
New York, United States
5 h-index
8 publications
2.6K citations
The University of Tokyo
Tokyo, Japan
5 h-index
14 publications
722 citations
Institute for Infocomm Research
Singapore, Singapore
4 h-index
14 publications
4.5K citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
7 publications
433 citations
1–8 of 247
Repository · 17 publications · 414 citations
12
h-index
JAMIA · 5 publications · 293 citations
5
h-index
Conference · 3 publications · 112 citations
3
h-index
3 publications · 66 citations
3
h-index
3 publications · 89 citations
3
h-index
1–5