Triple

T1533657
Position Surface form Disambiguated ID Type / Status
Subject Creuse E32501 entity
Predicate historicalRegion P915 FINISHED
Object Limousin E84116 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: Limousin | Statement: [Creuse, historicalRegion, Limousin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limousin
Context triple: [Creuse, historicalRegion, Limousin]
  • A. Limousin chosen
    Limousin is a former administrative region in central France known for its rural landscapes, cattle breeding, and historic towns such as Limoges and Tulle.
  • B. Charolais
    Charolais is a historic rural region in eastern France renowned for its high-quality beef cattle and rich agricultural traditions.
  • C. Bouvier
    Bouvier is the maiden surname of Jacqueline Kennedy Onassis, associated with a prominent American socialite and political family.
  • D. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • E. Ayrshire cattle
    Ayrshire cattle are a hardy, medium-sized dairy breed from southwest Scotland, renowned for their efficient milk production and adaptability to various climates and grazing conditions.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f8df00819086f34847e2170e12 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30942dc481908de85bd2ca30c0bd completed March 8, 2026, 8:17 a.m.
Created at: March 4, 2026, 7:26 p.m.