Triple

T9820696
Position Surface form Disambiguated ID Type / Status
Subject Loiret department E238522 entity
Predicate hasCity P316 FINISHED
Object Pithiviers E628264 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: Pithiviers | Statement: [Loiret department, hasCity, Pithiviers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pithiviers
Context triple: [Loiret department, hasCity, Pithiviers]
  • A. Pithiviers chosen
    Pithiviers is a small town in north-central France known for its historical architecture and traditional French pastries.
  • B. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • C. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • D. Melun
    Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
  • E. Chapeauroux
    Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb313134081908eb0ba3a22b22e2b completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d99859b5cc81908475fde408802607 completed April 11, 2026, 12:39 a.m.
Created at: March 30, 2026, 8:31 p.m.