Semantic Question Answering
Semantic Question Answering is a question answering approach that belongs to the class of methods leveraging deep semantic understanding of natural language, distinguished by its use of formal representations of meaning—such as logical forms, knowledge graphs, or ontological structures—to interpret questions and generate answers grounded in inferred or explicit semantic relationships.
277
Publications
19.6K
Citations
843
Authors
311
Institutions
Publications per year
2017–2026
96
Parents
277
GPT-3: Its Nature, Scope, Limits, and Consequences
Luciano Floridi, Massimo Chiriatti · Minds and Machines · 2020 · 2.2K citations · Full text
Data exchange: semantics and query answering
Ronald Fagin, Phokion G. Kolaitis, Renée J. Miller et al. · Theoretical Computer Science · 2004 · 1.2K citations
Towards a theory of natural language interfaces to databases
Ana-Maria Popescu, Oren Etzioni, Henry Kautz · 2003 · 521 citations
1–5 of 277
843
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311

The Open University
Milton Keynes, United Kingdom
11 h-index
32 publications
2.8K citations

Peking University
Beijing, China
7 h-index
16 publications
1.5K citations
University of Washington
Seattle, United States
7 h-index
19 publications
3.5K citations
Massachusetts Institute of Technology
Cambridge, United States
6 h-index
12 publications
570 citations
Microsoft (United States)
Redmond, United States
6 h-index
24 publications
4.5K citations
Stanford University
Stanford, United States
6 h-index
14 publications
664 citations
University of Southern California
Los Angeles, United States
5 h-index
12 publications
1.2K citations

Harbin Institute of Technology
Harbin, China
5 h-index
15 publications
901 citations
1–8 of 311
Repository · 11 publications · 248 citations
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6 publications · 267 citations
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5 publications · 596 citations
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5 publications · 349 citations
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5 publications · 82 citations
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