Triple

T3474521
Position Surface form Disambiguated ID Type / Status
Subject University of Bourges E73339 entity
Predicate locatedIn P40 FINISHED
Object Bourges E206721 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: Bourges | Statement: [University of Bourges, locatedIn, Bourges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bourges
Context triple: [University of Bourges, locatedIn, Bourges]
  • A. Bourges chosen
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • 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. Chapeauroux
    Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
  • D. Mâcon
    Mâcon is a historic town in eastern France’s Burgundy region, known for its wine production and picturesque setting along the Saône River.
  • E. Poitiers
    Poitiers is a historic city in western France known for its Romanesque architecture, medieval heritage, and role as a regional center in the Nouvelle-Aquitaine 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_69ad85b2fed48190948c8765e453d270 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb580d4c819080bcc0bccd1e18e2 completed March 8, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdf9f26be48190bf21b252a922ca69 completed March 21, 2026, 1:52 a.m.
Created at: March 8, 2026, 3:17 p.m.