Knowledge-to-text Generation
Knowledge-to-Text Generation is a natural language generation task that involves the automated production of coherent and contextually appropriate textual narratives from structured or semi-structured knowledge representations, distinguished by its focus on conveying factual information embedded in formal knowledge sources such as databases, ontologies, or knowledge graphs.
266
Publications
15.9K
Citations
873
Authors
275
Institutions
Publications per year
2017–2026
127
Parents
266
H. P. Grice · The Philosophical Review · 1957 · 2.7K citations
COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap et al. · 2019 · 865 citations · Full text
Learning semantic correspondences with less supervision
Percy Liang, Michael I. Jordan, Dan Klein · 2009 · 311 citations · Full text
1–5 of 266
873
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Athens University of Economics and Business, Greece
5 publications · 150 citations
5
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4
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1–5 of 873
275

University of Edinburgh
Edinburgh, United Kingdom
11 h-index
19 publications
957 citations
Columbia University
New York, United States
8 h-index
19 publications
931 citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
27 publications
604 citations
University of Southern California
Los Angeles, United States
6 h-index
13 publications
583 citations

University of Aberdeen
Aberdeen, United Kingdom
6 h-index
12 publications
427 citations

Harbin Institute of Technology
Harbin, China
5 h-index
8 publications
439 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
9 publications
272 citations
The University of Texas at Austin
Austin, United States
5 h-index
18 publications
2K citations
1–8 of 275
Repository · 31 publications · 899 citations
17
h-index
Conference · 8 publications · 476 citations
7
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Repository · 4 publications · 160 citations
4
h-index
3 publications · 74 citations
3
h-index
3 publications · 109 citations
3
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