Triple

T8974439
Position Surface form Disambiguated ID Type / Status
Subject Autódromo de Tocancipá E214349 entity
Predicate locatedIn P40 FINISHED
Object Tocancipá E38147 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: Tocancipá | Statement: [Autódromo de Tocancipá, locatedIn, Tocancipá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tocancipá
Context triple: [Autódromo de Tocancipá, locatedIn, Tocancipá]
  • A. Tocancipá chosen
    Tocancipá is a Colombian municipality in the department of Cundinamarca, known for its industrial activity, motorsport circuit, and proximity to Bogotá.
  • B. Guayaramerín
    Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
  • C. Tucupita
    Tucupita is a small Venezuelan city that serves as the capital of Delta Amacuro state and the main urban center near the Orinoco Delta.
  • D. Orocué
    Orocué is a small Colombian town and municipality located in the eastern plains region, known for its cattle ranching and proximity to the Meta River.
  • E. Caranavi
    Caranavi is a Bolivian town known as a key coffee-growing and agricultural hub in the Yungas region.
  • 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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6783abe48190840e652fc2acf28f completed April 1, 2026, 12:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc966f7d881908f4f80c2a0d820fe completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:02 p.m.