Triple

T1582573
Position Surface form Disambiguated ID Type / Status
Subject Departamento de Cundinamarca E33998 entity
Predicate hasMajorCity P316 FINISHED
Object Mosquera E36495 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: Mosquera | Statement: [Departamento de Cundinamarca, hasMajorCity, Mosquera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mosquera
Context triple: [Departamento de Cundinamarca, hasMajorCity, Mosquera]
  • A. Mosquera chosen
    Mosquera is a municipality in the department of Cundinamarca, Colombia, located near Bogotá and known for its growing industrial and residential development.
  • B. Espinal
    Espinal is a significant urban center in central Colombia known for its agricultural economy and cultural traditions within the Tolima Department.
  • C. Sogamoso
    Sogamoso is a Colombian city in the Andean region known historically as a major religious and cultural center of the Muisca civilization and today for its industry and mining.
  • D. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • E. Villapinzón
    Villapinzón is a Colombian town and municipality in the department of Cundinamarca, known for its leather industry and location in the Andean highlands.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908ef80a48190bd5a8e51c65e5588 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada967e01481908802baf2de7ad6a7 completed March 8, 2026, 4:52 p.m.
Created at: March 4, 2026, 7:27 p.m.