Triple

T10895056
Position Surface form Disambiguated ID Type / Status
Subject Kizh E257286 entity
Predicate neighboringGroup P5965 FINISHED
Object Serrano E46489 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: Serrano | Statement: [Kizh, neighboringGroup, Serrano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serrano
Context triple: [Kizh, neighboringGroup, Serrano]
  • A. Serrano chosen
    Serrano are an Indigenous people of Southern California traditionally inhabiting the San Bernardino Mountains and surrounding desert regions.
  • B. Serrano
    Serrano was a Chilean naval officer and war hero, notably associated with the naval battles of the War of the Pacific.
  • C. Poleñino
    Poleñino is a small municipality in the province of Huesca, Aragon, Spain, historically noted as the place where King Alfonso I of Aragon died.
  • D. Narón
    Narón is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its close ties to the nearby city of Ferrol and its role in the region’s industrial and service economy.
  • E. Canillejas
    Canillejas is a Madrid Metro station serving the Canillejas neighborhood in the San Blas-Canillejas district of Madrid, Spain.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75d0153408190bcba2d9b03d78804 completed April 9, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e15519e620819090e492861de6a567 completed April 16, 2026, 9:31 p.m.
Created at: April 8, 2026, 9:21 p.m.