Triple

T1464083
Position Surface form Disambiguated ID Type / Status
Subject Nièvre E31578 entity
Predicate borderedBy P224 FINISHED
Object Saône-et-Loire E29871 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: Saône-et-Loire | Statement: [Nièvre, borderedBy, Saône-et-Loire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saône-et-Loire
Context triple: [Nièvre, borderedBy, Saône-et-Loire]
  • A. Saône-et-Loire chosen
    Saône-et-Loire is a department in the Bourgogne-Franche-Comté region of eastern France, known for its historic towns, Romanesque churches, and Burgundy vineyards.
  • B. Côte d'Or
    Côte d'Or is a renowned wine-producing region in Burgundy, France, celebrated for its high-quality Pinot Noir and Chardonnay wines.
  • C. Sarthe
    Sarthe is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
  • D. Haute-Loire
    Haute-Loire is a rural department in south-central France, known for its volcanic landscapes, the upper Loire River valley, and historic towns such as Le Puy-en-Velay.
  • E. Drôme
    Drôme is a department in southeastern France known for its diverse landscapes, historic towns, and location between the Alps and the Rhône Valley.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c5b89708819084fb9ba4ff293b8b completed March 1, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e7c8a608190b3ca574c118e89b5 completed March 8, 2026, 5:51 a.m.
Created at: March 1, 2026, 8 p.m.