Triple

T840499
Position Surface form Disambiguated ID Type / Status
Subject Saône River E18164 entity
Predicate notableCityOnRiver P14915 FINISHED
Object Dijon E72631 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: Dijon | Statement: [Saône River, notableCityOnRiver, Dijon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dijon
Context triple: [Saône River, notableCityOnRiver, Dijon]
  • A. Dijon chosen
    Dijon is a historic city in eastern France renowned for its rich architectural heritage, former status as the capital of the Duchy of Burgundy, and its famous mustard.
  • B. 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.
  • C. Troyes
    Troyes is a historic city in northeastern France, known for its well-preserved medieval old town, half-timbered houses, and Gothic churches.
  • D. Besançon
    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.
  • E. Clermont-Ferrand
    Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
  • 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abe5d7848190b15e0cb343b6f4ba completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69acddfa1d48819081538d6505fa062c completed March 8, 2026, 2:24 a.m.
Created at: March 1, 2026, 7:38 p.m.