Triple

T4604131
Position Surface form Disambiguated ID Type / Status
Subject Gray E100388 entity
Predicate locatedIn P40 FINISHED
Object Haute-Saône department E136074 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: Haute-Saône department | Statement: [Gray, locatedIn, Haute-Saône department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haute-Saône department
Context triple: [Gray, locatedIn, Haute-Saône department]
  • A. Haute-Saône chosen
    Haute-Saône is a rural department in the Bourgogne-Franche-Comté region of eastern France, known for its forests, rivers, and historic villages.
  • B. Vosges department
    The Vosges department is an administrative region in northeastern France known for its forested mountains, lakes, and role as the source area for several rivers.
  • C. Jura department
    The Jura department is an administrative region in eastern France known for its mountainous landscapes, forests, and lakes within the Jura Mountains.
  • D. Drôme department
    The Drôme department is an administrative region in southeastern France, known for its historic towns, vineyards, and proximity to the Rhône Valley.
  • E. Isère department
    Isère department is an administrative region in southeastern France, known for its Alpine landscapes, winter sports resorts, and the city of Grenoble.
  • 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_69bd43cce1e08190a07d53af6a9b6c24 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5999f9c88190a43309573df61159 completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa676b0081909f56049f466e1197 completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.