Triple

T17802249
Position Surface form Disambiguated ID Type / Status
Subject University of Franche-Comté E444458 entity
Predicate hasCampus P116 FINISHED
Object Belfort 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: Belfort | Statement: [University of Franche-Comté, hasCampus, Belfort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belfort
Context triple: [University of Franche-Comté, hasCampus, Belfort]
  • A. 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."
  • B. Montélimar
    Montélimar is a town in southeastern France, known as the "gateway to Provence" and famous for its traditional nougat confectionery.
  • C. Dijon
    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.
  • D. City of Belfort chosen
    The City of Belfort is a historic commune in northeastern France, known for its strategic fortress, rich military heritage, and the monumental Lion of Belfort sculpture by Frédéric Bartholdi.
  • E. Épinal
    Épinal is a historic town in northeastern France, known for its traditional image-printing industry and picturesque setting in the Vosges region.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e488005a288190b7a2cffa590d2557 completed April 19, 2026, 7:45 a.m.
Created at: April 10, 2026, 10:13 a.m.