Generation of Training Examples for Tabular Natural Language Inference

Summary: Tenet automates TNLI data generation on tables via SQL-based evidence-queries and semantic-queries for varied reasoning. It generates counterfactuals by injecting errors and uses table-only generation to yield diverse, human-like TNLI examples, competitive with manually written data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6807
Venue: SIGMOD
Year: 2023
Pagerank: 5.3256746e-05
Overall Rank: 8,978 | 38.62%
DOI: 10.1145/3626730

Incoming Non-self Citations Over Time

Authors

1. Jean-Flavien Bussotti (EURECOM)
2. Enzo Veltri (University of Basilicata)
3. Donatello Santoro (University of Basilicata)
4. Paolo Papotti (EURECOM)

BibTeX Citation

@inproceedings{bussotti_sigmod23,
        title = {{Generation of Training Examples for Tabular Natural Language Inference}},
        author = {Bussotti, Jean-Flavien and Veltri, Enzo and Santoro, Donatello and Papotti, Paolo},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3626730},
        url = {https://dl.acm.org/doi/10.1145/3626730},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,081	SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation	2026	VLDB	5.302893e-05
10,439	Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations	2026	SIGMOD	5.0723324e-05
13,390	Accelerating Tabular Inference: Training Data Generation with TENET	2025	VLDB	-

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,192	Query From Examples: An Iterative, Data-Driven Approach to Query Construction	2015	VLDB	0.00011699676
1,319	Reverse Engineering Complex Join Queries	2013	SIGMOD	0.00011146794
2,085	DBPal: A Fully Pluggable NL2SQL Training Pipeline	2020	SIGMOD	9.1775632e-05
3,314	Reverse Engineering Aggregation Queries	2017	VLDB	7.5151146e-05
3,352	A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems	2021	SIGMOD	7.4756413e-05
4,465	From BERT to GPT-3 Codex: Harnessing the Potential of Very Large Language Models for Data Management	2022	VLDB	6.6698198e-05
4,640	Reverse Engineering SPJ-Queries from Examples	2017	PODS	6.5706572e-05
4,842	Transformers for Tabular Data Representation: A Tutorial on Models and Applications	2022	VLDB	6.4662743e-05
5,177	An In-Depth Benchmarking of Text-to-SQL Systems	2021	SIGMOD	6.3149695e-05
8,624	Exploratory Training: When Annotators Learn About Data	2023	SIGMOD	5.3827024e-05
11,604	Pythia: Unsupervised Generation of Ambiguous Textual Claims from Relational Data	2022	SIGMOD	5.0723324e-05

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