Triple

T8082245
Position Surface form Disambiguated ID Type / Status
Subject Granada CF E188644 entity
Predicate basedIn P40 FINISHED
Object Granada E15680 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: Granada | Statement: [Granada CF, basedIn, Granada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Granada
Context triple: [Granada CF, basedIn, Granada]
  • A. Granada
    Granada is a municipality in the Cundinamarca Department of central Colombia, known for its agricultural economy and proximity to the Bogotá metropolitan area.
  • B. Granada chosen
    Granada is a historic city in southern Spain, renowned as the last stronghold of Muslim rule on the Iberian Peninsula and home to the famed Alhambra palace.
  • C. Granada
    Granada is a Colombian town and municipality in the Meta Department, known for its agricultural economy and role as a regional service center in the Llanos Orientales.
  • D. Granada
    Granada is a historic colonial city in western Nicaragua, known for its well-preserved Spanish architecture and location on the shores of Lake Nicaragua.
  • E. Seville
    Seville is a historic Spanish city in Andalusia renowned for its rich Moorish and Christian heritage, iconic landmarks like the Giralda and Alcázar, and vibrant cultural traditions such as flamenco.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40a699388190a5b8e26524ae43e5 completed March 31, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd946a5e188190b2ef0a07a885ade7 completed April 1, 2026, 9:55 p.m.
Created at: March 30, 2026, 5:28 p.m.