Triple

T1695224
Position Surface form Disambiguated ID Type / Status
Subject Cher E36641 entity
Predicate borders P224 FINISHED
Object Nièvre E31578 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: Nièvre | Statement: [Cher, borders, Nièvre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nièvre
Context triple: [Cher, borders, Nièvre]
  • A. Nièvre chosen
    Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
  • B. Yonne
    Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
  • C. Loir
    The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
  • D. Allier River
    The Allier River is a major river in central France, known for its largely unspoiled natural course and as a tributary of the Loire.
  • E. Loire
    The Loire is the longest river in France, renowned for its scenic valley dotted with historic châteaux and vineyards.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b3b8908190afc3f9e4a384684f completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6529905081909bd9e7c51fc21f77 completed March 10, 2026, 12:26 a.m.
Created at: March 4, 2026, 7:30 p.m.