Triple

T10369908
Position Surface form Disambiguated ID Type / Status
Subject Château de Blois E244353 entity
Predicate locatedIn P40 FINISHED
Object Blois E101372 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: Blois | Statement: [Château de Blois, locatedIn, Blois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blois
Context triple: [Château de Blois, locatedIn, Blois]
  • A. Blois chosen
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • B. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • C. 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.
  • D. Pithiviers
    Pithiviers is a small town in north-central France known for its historical architecture and traditional French pastries.
  • E. La Châtre
    La Châtre is a small historic town in central France known for its picturesque medieval streets and its association with the writer George Sand.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9725fa08190816bedf0acefbc2a completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f416ab88e48190b3089caab7987191 completed May 1, 2026, 2:57 a.m.
Created at: April 6, 2026, 12:01 p.m.