Triple

T1688513
Position Surface form Disambiguated ID Type / Status
Subject Sabana de Bogotá E36496 entity
Predicate contains P35 FINISHED
Object Facatativá E33388 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: Facatativá | Statement: [Sabana de Bogotá, contains, Facatativá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Facatativá
Context triple: [Sabana de Bogotá, contains, Facatativá]
  • A. Facatativá chosen
    Facatativá is a Colombian city in the Andean region, known for its proximity to Bogotá and the nearby Piedras del Tunjo archaeological park.
  • B. Tocaima
    Tocaima is a historic Colombian town in the Cundinamarca Department, known for its warm climate and thermal springs.
  • C. Caparrapí
    Caparrapí is a municipality in central Colombia known for its rural character and location within the Andean region of the Cundinamarca Department.
  • D. Puerto Boyacá
    Puerto Boyacá is a Colombian river port town on the Magdalena River known for its oil industry and strategic commercial importance.
  • E. Bejucal
    Bejucal is a Cuban town and municipality known for its historic role in the island’s early railway system and its traditional “Charangas de Bejucal” carnival festivities.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6296655c8190835ec0d20f7460ca completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeac637748190b67ddd9eedc3698d completed March 8, 2026, 9:31 p.m.
Created at: March 4, 2026, 7:29 p.m.