Triple

T8296607
Position Surface form Disambiguated ID Type / Status
Subject A20 motorway E194234 entity
Predicate passesThrough P225 FINISHED
Object Châteauroux E43984 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: Châteauroux | Statement: [A20 motorway, passesThrough, Châteauroux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Châteauroux
Context triple: [A20 motorway, passesThrough, Châteauroux]
  • A. Châteauroux chosen
    Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
  • B. Chapeauroux
    Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
  • 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. Montluçon
    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.
  • E. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7df887148190bddc2609bc885cb4 completed March 31, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc6dc4008819084eff0960917494c completed April 2, 2026, 1:31 a.m.
Created at: March 30, 2026, 5:53 p.m.