Joint Entity Recognition
Joint Entity Recognition is a methodological framework in natural language processing that simultaneously identifies and classifies multiple types of named entities within a text, distinguishing itself from pipeline approaches by modeling entity boundaries and types in a unified, interdependent manner.
148
Publications
11.4K
Citations
540
Authors
194
Institutions
Publications per year
2017–2026
116
Parents
148
1–5 of 148
540
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194

Harbin Institute of Technology
Harbin, China
9 h-index
17 publications
855 citations
Tsinghua University
Beijing, China
7 h-index
20 publications
1.4K citations

National University of Defense Technology
Changsha, China
5 h-index
19 publications
753 citations
Wuhan University
Wuhan, China
5 h-index
9 publications
943 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
16 publications
2.4K citations

Peking University
Beijing, China
5 h-index
8 publications
871 citations

Cornell University
Ithaca, United States
4 h-index
9 publications
1.1K citations
Stanford University
Stanford, United States
4 h-index
6 publications
174 citations
1–8 of 194
Repository · 13 publications · 513 citations
12
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Conference · 8 publications · 539 citations
8
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7 publications · 289 citations
7
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4 publications · 395 citations
4
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4 publications · 58 citations
4
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1–5