Triple

T8341393
Position Surface form Disambiguated ID Type / Status
Subject Chinchiná E195922 entity
Predicate region P40 FINISHED
Object Eje Cafetero E371825 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: Eje Cafetero | Statement: [Chinchiná, region, Eje Cafetero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eje Cafetero
Context triple: [Chinchiná, region, Eje Cafetero]
  • A. Eje Cafetero chosen
    Eje Cafetero is a mountainous region in central Colombia renowned for its coffee plantations, lush landscapes, and role as the heart of the country’s coffee production and culture.
  • B. Cauca
    Cauca is a department in southwestern Colombia known for its diverse geography, indigenous communities, and cultural richness.
  • C. Cauca
    Cauca was an ancient Roman town in Hispania, located in what is now Coca in the province of Segovia, Spain.
  • D. Northwestern Colombia
    Northwestern Colombia is a geographic region of Colombia bordering the Caribbean Sea and Panama, known for its coastal lowlands, tropical climate, and strategic location as a gateway between South and Central America.
  • E. Valle de Aburrá
    Valle de Aburrá is a densely populated valley in the Colombian Andes that encompasses the city of Medellín and its surrounding metropolitan area.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fe8989481909b32d4bfd586372d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc72bc43c81909d95c7eb6aefc403 completed April 2, 2026, 1:32 a.m.
Created at: March 30, 2026, 5:58 p.m.