Triple

T2180743
Position Surface form Disambiguated ID Type / Status
Subject Centre-Val de Loire E49035 entity
Predicate containsDepartment P1467 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: [Centre-Val de Loire, containsDepartment, Loiret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loiret
Context triple: [Centre-Val de Loire, containsDepartment, 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. Nièvre
    Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
  • 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_69a88aa72d348190a9544bb5b8a4e71d completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbef0e2f0819080ca457fe3b8b419 completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69b37376d7288190a25c81a001556019 completed March 13, 2026, 2:16 a.m.
Created at: March 4, 2026, 7:45 p.m.