Triple

T11362002
Position Surface form Disambiguated ID Type / Status
Subject King of Brittany E269106 entity
Predicate seatOfPower P761 FINISHED
Object Vannes E162998 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Vannes | Statement: [King of Brittany, seatOfPower, Vannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vannes
Context triple: [King of Brittany, seatOfPower, Vannes]
  • A. Vannes chosen
    Vannes is a historic coastal city in northwestern France known for its well-preserved medieval old town and harbor on the Gulf of Morbihan.
  • B. Quimper
    Quimper is a historic city in western France known for its medieval old town, Gothic cathedral, and traditional Breton culture.
  • C. Rennes
    Rennes is the capital city of France’s Brittany region, known for its historic medieval center, vibrant student population, and role as a major cultural and economic hub in western France.
  • D. Landerneau
    Landerneau is a historic town in the Finistère department of Brittany in northwestern France, known for its medieval architecture and distinctive inhabited bridge over the Élorn River.
  • E. Le Croisic
    Le Croisic is a coastal town and popular seaside resort on the Atlantic coast of western France, known for its historic harbor and scenic peninsula.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea442e5c8190babfde25540b27e9 completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58bb3bd648190affa7ee85027c958 completed April 20, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:33 p.m.