Triple

T6686134
Position Surface form Disambiguated ID Type / Status
Subject Deux-Sèvres E152102 entity
Predicate contains P35 FINISHED
Object Bressuire E727168 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: Bressuire | Statement: [Deux-Sèvres, contains, Bressuire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bressuire
Context triple: [Deux-Sèvres, contains, Bressuire]
  • A. Bressuire chosen
    Bressuire is a historic town in western France known for its medieval castle and role as an administrative center in the Deux-Sèvres department.
  • B. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • C. Plessis-lez-Tours
    Plessis-lez-Tours is a historic former royal residence near Tours in central France, best known as the place where King Louis XI died.
  • D. Arnouville
    Arnouville is a commune in the Val-d'Oise department in the northern suburbs of Paris, France.
  • E. Bièvres
    Bièvres is a commune in the Essonne department in the southern suburbs of Paris, France, known for its picturesque valley and proximity to the capital.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14cd6748190aad4badd5f253478 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cde6789ec081909b051b8ce1bde35d completed April 2, 2026, 3:46 a.m.
Created at: March 27, 2026, 2:04 p.m.