Triple

T664015
Position Surface form Disambiguated ID Type / Status
Subject Monserrate Sanctuary E12819 entity
Predicate locatedIn P40 FINISHED
Object Bogotá 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 | Statement: [Monserrate Sanctuary, locatedIn, Bogotá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogotá
Context triple: [Monserrate Sanctuary, locatedIn, Bogotá]
  • 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. Cali
    Cali is a major city in southwestern Colombia known as an important economic center and the country’s capital of salsa.
  • C. Medellín
    Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
  • D. Caracas
    Caracas is the capital and largest city of Venezuela, known as a major political, cultural, and economic center in northern South America.
  • E. Quito
    Quito is the high-altitude Andean city that serves as Ecuador’s political and cultural center, renowned for its well-preserved colonial historic center and dramatic mountain setting.
  • 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_69a493355dec819098d4244b2fa34885 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49fd1f0ec819087003d30bbab2fa6 completed March 1, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c398cc748190ab720263096064ef completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:36 p.m.