Triple

T947280
Position Surface form Disambiguated ID Type / Status
Subject Usaquén E20440 entity
Predicate locatedIn P40 FINISHED
Object Bogotá Capital District E1526 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: Bogotá Capital District | Statement: [Usaquén, locatedIn, Bogotá Capital District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogotá Capital District
Context triple: [Usaquén, locatedIn, Bogotá Capital District]
  • A. Bogotá chosen
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • B. Medellín
    Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
  • C. Cali
    Cali is a major city in southwestern Colombia known as an important economic center and the country’s capital of salsa.
  • D. Anapoima
    Anapoima is a warm-climate resort town and popular weekend getaway located in the Cundinamarca department of central Colombia.
  • E. Santa Marta
    Santa Marta is a historic Caribbean port city in northern Colombia and one of the oldest surviving Spanish settlements in South America.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3be19448190a8863fce3d152430 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c017e148190b368419cff3872f6 completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:40 p.m.