Triple

T4718921
Position Surface form Disambiguated ID Type / Status
Subject Vallespir E104714 entity
Predicate administrativeCenter P1474 FINISHED
Object Céret E88275 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: Céret | Statement: [Vallespir, administrativeCenter, Céret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Céret
Context triple: [Vallespir, administrativeCenter, Céret]
  • A. Céret chosen
    Céret is a historic town in southern France near the Spanish border, renowned for its modern art museum and its association with early 20th-century artists like Picasso and Braque.
  • B. Marvejols
    Marvejols is a historic town in southern France’s Lozère department, known for its medieval heritage and location near the Aubrac and Margeride regions.
  • C. Saint-Girons
    Saint-Girons is a small town in the Ariège department of southwestern France, situated in the foothills of the Pyrenees.
  • D. Limoux
    Limoux is a small town in southern France known for its sparkling wine Blanquette de Limoux and its long-running carnival traditions.
  • E. Camprodon
    Camprodon is a small town in the Catalan Pyrenees of northeastern Spain, known for its scenic mountain setting and historic Romanesque architecture.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd642779a08190b01e588d515cf498 completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be39f7316c8190a6ecd65b707d3fbe completed March 21, 2026, 6:25 a.m.
Created at: March 20, 2026, 1:18 p.m.