Triple

T12604205
Position Surface form Disambiguated ID Type / Status
Subject Vicenç Ferrer E300933 entity
Predicate deathPlace P21 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: [Vicenç Ferrer, deathPlace, Vannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vannes
Context triple: [Vicenç Ferrer, deathPlace, 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954e6e20481908bca684c4b497c48 completed April 10, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ea99ac88190bc0220a18c58f755 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:10 p.m.