Triple

T15867165
Position Surface form Disambiguated ID Type / Status
Subject Politics of the Basque Country E384742 entity
Predicate hasConstituency P1971 FINISHED
Object Biscay E159064 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: Biscay | Statement: [Politics of the Basque Country, hasConstituency, Biscay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biscay
Context triple: [Politics of the Basque Country, hasConstituency, Biscay]
  • A. Biscay chosen
    Biscay is a coastal province in northern Spain, known for its capital Bilbao and its role as a historic and cultural center of the Basque Country.
  • B. Leioa
    Leioa is a suburban municipality in the Basque Country in northern Spain, located near Bilbao in the province of Biscay.
  • C. Abia
    Abia is a state in southeastern Nigeria known for its commercial hub Aba and its role in regional trade and industry.
  • D. Zuberoa
    Zuberoa is the Basque-language name for Soule, a small historical and cultural province of the Basque Country located in the French Pyrenees.
  • E. Garrotxa
    Garrotxa is a comarca (county) in northeastern Catalonia, Spain, known for its volcanic landscape, beech forests, and the medieval town of Besalú.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155603e908190acad1bce2eb6e210 completed April 16, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa947ba3881909c602f2fc60dd6e8 completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:50 a.m.