Triple

T1688510
Position Surface form Disambiguated ID Type / Status
Subject Sabana de Bogotá E36496 entity
Predicate contains P35 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: [Sabana de Bogotá, contains, Mosquera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mosquera
Context triple: [Sabana de Bogotá, contains, 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6296655c8190835ec0d20f7460ca completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf3608208190a27b0f949da83fcd completed March 8, 2026, 8:42 p.m.
Created at: March 4, 2026, 7:29 p.m.