Triple

T13753136
Position Surface form Disambiguated ID Type / Status
Subject Antoine César Becquerel E330404 entity
Predicate placeOfBirth P1 FINISHED
Object Loiret E210466 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: Loiret | Statement: [Antoine César Becquerel, placeOfBirth, Loiret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loiret
Context triple: [Antoine César Becquerel, placeOfBirth, Loiret]
  • A. Loiret chosen
    Loiret is a department in north-central France, named after the Loiret River and known for its historic towns and proximity to the Loire Valley.
  • B. Yonne
    Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
  • C. Loir
    The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
  • D. Loire
    The Loire is the longest river in France, renowned for its scenic valley dotted with historic châteaux and vineyards.
  • E. Loire
    Loire is a department in central-eastern France named after the Loire River, known for its varied landscapes, industrial cities like Saint-Étienne, and historical ties to the broader Loire Valley region.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0215cfa08190aaed8b089aff217b completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd8a9c41908190b789765861bd9924 completed May 8, 2026, 7:02 a.m.
Created at: April 9, 2026, 10:09 p.m.