NLProveNAns: Natural Language Provenance for Non-Answers
Summary: NLProveNAns, a natural-language DB interface, explains non-answers to non-expert users. It highlights NL-query fragments responsible for missing results and supports two why-not provenance flavors: frontier-picky (brief) and why-not polynomial (detailed). (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Daniel Deutch
- 2. Nave Frost
- 3. Amir Gilad
- 4. Tomer Haimovich
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,678 | To Not Miss the Forest for the Trees - A Holistic Approach for Explaining Missing Answers over Nested Data | 2021 | SIGMOD | 4.6813062e-05 |
| 9,704 | Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb | 2021 | VLDB | 4.3005882e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 206 | Constructing an Interactive Natural Language Interface for Relational Databases | 2015 | VLDB | 0.00034667032 |
| 487 | Why Not? | 2009 | SIGMOD | 0.00022050218 |
| 6,573 | EFQ: Why-Not Answer Polynomials in Action | 2015 | VLDB | 5.0058435e-05 |
| 6,662 | Selective Provenance for Datalog Programs Using Top-K Queries | 2015 | VLDB | 4.9704872e-05 |
| 9,622 | NLProv: Natural Language Provenance | 2016 | VLDB | 4.3163112e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,696 | Approximate Summaries for Why and Why-not Provenance | 2020 | VLDB | 4.9581958e-05 |
| 11,735 | QuestPro: Queries in SPARQL Through Provenance | 2018 | VLDB | 4.1945683e-05 |
| 11,551 | Toward Pure Natural Language Interaction with Databases | 2020 | CIDR | 4.1945683e-05 |
| 1,125 | How to ConQueR Why-Not Questions | 2010 | SIGMOD | 0.00013845652 |
| 487 | Why Not? | 2009 | SIGMOD | 0.00022050218 |
| 5,418 | High-Level Why-Not Explanations using Ontologies | 2015 | PODS | 5.5178123e-05 |
| 11,733 | Provenance Summaries for Answers and Non-Answers | 2018 | VLDB | 4.1945683e-05 |
| 652 | On the Provenance of Non-Answers to Queries over Extracted Data | 2008 | VLDB | 0.00018634477 |
| 4,851 | Provenance for Natural Language Queries | 2017 | VLDB | 5.8768322e-05 |
| 9,622 | NLProv: Natural Language Provenance | 2016 | VLDB | 4.3163112e-05 |