CypherLens: An Interactive Demo for Evaluating and Diagnosing NL-to-Cypher Systems
Summary: CypherLens moves NL-to-Cypher evaluation beyond brittle execution accuracy with normalized outputs, column alignment, and Exact/Soft Match metrics. A Cypher-specific classifier and diagnoser expose actionable semantic/syntactic failures interactively at query and dataset levels. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Zahra Mohammadi (Temple University)
- 2. Ali Ansari (Temple University)
- 3. Longin Latecki (Temple University)
- 4. Eduard Dragut (Temple University)
BibTeX Citation
@article{mohammadi_vldb26,
title = {{CypherLens: An Interactive Demo for Evaluating and Diagnosing NL-to-Cypher Systems}},
author = {Mohammadi, Zahra and Ansari, Ali and Latecki, Longin and Dragut, Eduard},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4558--4561},
doi = {10.14778/3827998.3828065},
url = {https://doi.org/10.14778/3827998.3828065},
year = {2026}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 419 | Cypher: An Evolving Query Language for Property Graphs | 2018 | SIGMOD | 0.0001854669 |
| 2,348 | The Dawn of Natural Language to SQL: Are We Fully Ready? | 2024 | VLDB | 8.6009821e-05 |
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