Triple

T10641975
Position Surface form Disambiguated ID Type / Status
Subject Dijon Academy of Sciences, Arts and Letters E250743 entity
Predicate regionServed P82 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: [Dijon Academy of Sciences, Arts and Letters, regionServed, Dijon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dijon
Context triple: [Dijon Academy of Sciences, Arts and Letters, regionServed, 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. Mâcon
    Mâcon is a historic town in eastern France’s Burgundy region, known for its wine production and picturesque setting along the Saône River.
  • C. 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.
  • D. Troyes
    Troyes is a historic city in northeastern France, known for its well-preserved medieval old town, half-timbered houses, and Gothic churches.
  • E. Belfort
    Belfort is the surname of Jordan Belfort, the American former stockbroker, motivational speaker, and author whose high-profile fraud case inspired the film "The Wolf of Wall Street."
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfce1ddc8190893fe6f7b047b56b completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5424a26688190a49c3920d0edb546 completed April 19, 2026, 8:59 p.m.
Created at: April 8, 2026, 9:05 p.m.