Triple

T16684780
Position Surface form Disambiguated ID Type / Status
Subject Pierre Orefice E405432 entity
Predicate basedIn P40 FINISHED
Object Nantes E16517 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: Nantes | Statement: [Pierre Orefice, basedIn, Nantes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nantes
Context triple: [Pierre Orefice, basedIn, Nantes]
  • A. Nantes chosen
    Nantes is a historic port city in western France on the Loire River, known for its maritime heritage, cultural institutions, and vibrant arts scene.
  • B. 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.
  • C. Clermont-Ferrand
    Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
  • D. Rodez
    Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
  • E. La Rochelle
    La Rochelle is a historic French Atlantic port city that became a major stronghold and refuge for Huguenots during the French Wars of Religion.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37d71a66881908c8d06cc074fdf29 completed April 18, 2026, 12:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c291e2008190b41a989c5c6e2860 completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:19 a.m.