Triple

T18122632
Position Surface form Disambiguated ID Type / Status
Subject Bourg-en-Bresse railway station E433779 entity
Predicate connectsTo P845 FINISHED
Object Besançon NE NERFINISHED

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: Besançon | Statement: [Bourg-en-Bresse railway station, connectsTo, Besançon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Besançon
Context triple: [Bourg-en-Bresse railway station, connectsTo, Besançon]
  • A. Besançon chosen
    Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational center.
  • B. Épinal
    Épinal is a historic town in northeastern France, known for its traditional image-printing industry and picturesque setting in the Vosges region.
  • C. Brioude
    Brioude is a historic town in south-central France known for its Romanesque Basilica of Saint-Julien and its location in the Haute-Loire department of the Auvergne region.
  • D. Bourg-en-Bresse
    Bourg-en-Bresse is a historic town in eastern France known as the capital of the Ain department, noted for its Renaissance architecture and the royal monastery of Brou.
  • E. Mulhouse
    Mulhouse is an industrial city in northeastern France near the Swiss and German borders, known for its textile heritage and major technical museums.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddeb2d7881909326cb9d2f5e2fb5 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:28 a.m.