Triple

T8112781
Position Surface form Disambiguated ID Type / Status
Subject Almeidas Province E189395 entity
Predicate containsMunicipality P852 FINISHED
Object Villapinzón E40578 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: Villapinzón | Statement: [Almeidas Province, containsMunicipality, Villapinzón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Villapinzón
Context triple: [Almeidas Province, containsMunicipality, Villapinzón]
  • A. Villapinzón chosen
    Villapinzón is a Colombian town and municipality in the department of Cundinamarca, known for its leather industry and location in the Andean highlands.
  • B. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • C. Fusagasugá
    Fusagasugá is a Colombian city in the department of Cundinamarca, known for its mild climate, flower cultivation, and role as an important commercial and agricultural center near Bogotá.
  • D. Guarequena
    Guarequena is an alternative name for the Warekena language, an indigenous Arawakan language spoken in parts of Brazil and Venezuela.
  • E. Cucunubá
    Cucunubá is a small colonial-era town in the Cundinamarca department of Colombia, known for its traditional wool textiles and scenic Andean highland landscapes.
  • 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_69ca82baad008190ab2859712b9b1607 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb432d7dfc8190b9c980f32c7b4623 completed March 31, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd948fcf90819090c80e1ac4ac1b0c completed April 1, 2026, 9:56 p.m.
Created at: March 30, 2026, 5:32 p.m.