BLINKG - Schema-Distant - Entity Class: leaderboard
Identifying the ontology class of each entity to be generated in the schema-distant scenario (an XML entry from the Spanish CODICE procurement platform mapped to a subset of the EU eProcurement Ontology) of BLINKG (Castedo et al., Universidade de Santiago de Compostela, 2026), where an LLM fills in the knowledge-graph construction mappings for given input data and an ontology. F1 in percent against 8 gold mappings, judged by knowledge-graph experts and macro-averaged over three runs at temperature 0.3; higher is better.
Metric: F1 (%; expert-validated mappings for the ontology class of each generated entity; 8 gold task instances; a Spanish CODICE procurement XML entry mapped to a subset of the eProcurement Ontology; macro-average of three runs). Source: arxiv.org. Saturation forecast: Estimated already saturated. 6 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | O3 | 54 | #224 |
| 2 | Gemini 2.5 Pro | 45 | #262 |
| 3 | GPT-4o | 26 | #741 |
| 4 | Llama 3.3 70B Instruct | 18 | #1353 |
| 5 | Mixtral 8x22B Instruct | 5 | #2052 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=blinkg-schema-distant-entity-class · How It Works · Data refreshed daily, snapshot 2026-11-12.