Triple

T956773
Position Surface form Disambiguated ID Type / Status
Subject Narcos E20641 entity
Predicate settingLocation P40 FINISHED
Object Medellín E73076 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: Medellín | Statement: [Narcos, settingLocation, Medellín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medellín
Context triple: [Narcos, settingLocation, Medellín]
  • A. Medellín chosen
    Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
  • B. Bogotá
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • C. Cali
    Cali is a major city in southwestern Colombia known as an important economic center and the country’s capital of salsa.
  • D. Santa Marta
    Santa Marta is a historic Caribbean port city in northern Colombia and one of the oldest surviving Spanish settlements in South America.
  • E. Barranquilla
    Barranquilla is a major port city on Colombia’s Caribbean coast, known for its vibrant culture and famous Carnival festival.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3f981bc819098125554eeeb6375 completed March 1, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5e9b74e481908c7d8256bd180d73 completed March 7, 2026, 5:21 p.m.
Created at: March 1, 2026, 7:40 p.m.