Doc2DB-Bench - Transitive Inference: leaderboard

The Transitive Inference capability of Doc2DB-Bench (2026), document-to-database construction: relationship-table cells annotated as requiring links implied through intermediate records, scored by cell-level F1 in percent; higher is better.

Metric: Cell-level F1 (%; relation-table cells annotated with the Transitive Inference capability of the inter-table taxonomy (Section 5.3); 203 synthesized long-document instances over 42 database schemas from BIRD and Spider in seven domain groups; identical prompts, greedy decoding at temperature 0; cells aligned by global maximum-weight tuple matching, a cell matching on exact numeric equality or at least 90 percent string similarity). Source: arxiv.org. Saturation forecast: Around February 2027. 8 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.478.47#123
2Gemini 2.5 Pro70.82#266
3GPT-4o65.51#741
4Claude Opus 4.659.48#102
5Llama 3.1 70B Instruct57.83#1546
6DeepSeek V4 Flash57.35#258
7Qwen 3 Max53.78#403
8Qwen 2.5 14B Instruct40.8#1732

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=doc2db-bench-transitive-inference · How It Works · Data refreshed daily, snapshot 2026-11-13.