Triple

T15178475
Position Surface form Disambiguated ID Type / Status
Subject La Cathédrale E362674 entity
Predicate setting P1957 FINISHED
Object Chartres E153197 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: Chartres | Statement: [La Cathédrale, setting, Chartres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chartres
Context triple: [La Cathédrale, setting, Chartres]
  • A. Chartres chosen
    Chartres is a historic city in northern France renowned for its well-preserved medieval old town and its UNESCO-listed Gothic cathedral, famed for its stained glass windows.
  • B. Chartres
    Chartres is a small rural settlement located on West Falkland in the Falkland Islands.
  • C. Cholet
    Cholet is a town in western France’s Maine-et-Loire department, known historically for its textile industry and as part of the Pays de la Loire region.
  • D. Saintes
    Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
  • E. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00663b4148190b647592eda315d1d completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec89061548190b0b10da00b8d937e completed May 9, 2026, 5:39 a.m.
Created at: April 10, 2026, 3:09 a.m.