Triple

T10331287
Position Surface form Disambiguated ID Type / Status
Subject TER Auvergne-Rhône-Alpes services E242878 entity
Predicate connectsCity P4245 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: [TER Auvergne-Rhône-Alpes services, connectsCity, Montluçon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montluçon
Context triple: [TER Auvergne-Rhône-Alpes services, connectsCity, 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7fcaf4c8190bdcfcb953d88ea2f completed April 7, 2026, 10:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69f12f646ec88190ab4745c52798b599 completed April 28, 2026, 10:06 p.m.
Created at: April 6, 2026, 11:52 a.m.