Triple

T11497213
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Montluçon E272566 entity
Predicate capital P234 FINISHED
Object Montluçon E52473 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: Montluçon | Statement: [arrondissement of Montluçon, capital, Montluçon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montluçon
Context triple: [arrondissement of Montluçon, capital, Montluçon]
  • A. Montluçon chosen
    Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
  • B. Châteauroux
    Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
  • C. Châtellerault
    Châtellerault is a historic town in western France, known for its former royal arms factory and its role as an important industrial and transport hub in the Vienne department.
  • D. Chapeauroux
    Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
  • E. Guéret
    Guéret is a small city in central France that serves as the capital of the Creuse department 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85de27db081909ccdb4ab0ef75bdb completed April 10, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f76b9112948190a0dd747a67f8206a completed May 3, 2026, 3:36 p.m.
Created at: April 8, 2026, 9:36 p.m.