Triple

T15756210
Position Surface form Disambiguated ID Type / Status
Subject provincial authorities of Biscay E381973 entity
Predicate administers P123 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: [provincial authorities of Biscay, administers, Biscay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biscay
Context triple: [provincial authorities of Biscay, administers, 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b1ff4881909d5240d1d30f5c8b completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff87714a8481909f8489c73ac89c11 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:47 a.m.