Triple

T5019477
Position Surface form Disambiguated ID Type / Status
Subject Steve Murphy (Narcos character) E112813 entity
Predicate operationalLocation P6602 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: [Steve Murphy (Narcos character), operationalLocation, Bogotá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogotá
Context triple: [Steve Murphy (Narcos character), operationalLocation, 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. Bucaramanga
    Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
  • E. La Candelaria, Bogotá
    La Candelaria, Bogotá is the historic colonial center of Colombia’s capital city, known for its preserved architecture, cultural institutions, and vibrant political and academic life.
  • 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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd77c9fc7c8190b165a5cfd5889ba8 completed March 20, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed90afc5c8190b205341d1e9dc7bc completed March 21, 2026, 5:44 p.m.
Created at: March 20, 2026, 1:35 p.m.