Triple

T3702405
Position Surface form Disambiguated ID Type / Status
Subject Julián Ruiz Gabiña E80809 entity
Predicate placeOfActivity P1527 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: [Julián Ruiz Gabiña, placeOfActivity, Biscay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biscay
Context triple: [Julián Ruiz Gabiña, placeOfActivity, 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. Gipuzkoa
    Gipuzkoa is a coastal province in northern Spain known for its Basque culture, rugged landscapes, and the city of San Sebastián.
  • C. Navarre
    Navarre is an autonomous community and historical region in northern Spain known for its diverse landscapes, rich cultural traditions, and capital city of Pamplona.
  • D. Orduña
    Orduña is a historic town in the Basque Country of northern Spain, known for its medieval heritage and strategic location along traditional trade routes.
  • E. Irrua
    Irrua is a prominent town in southern Nigeria known for hosting the Irrua Specialist Teaching Hospital and serving as an important local commercial and administrative center in Edo State.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc54925b48190b23d2a14ef825abc completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db041370819084b04e46d95ca966 completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:33 p.m.