Triple

T1534497
Position Surface form Disambiguated ID Type / Status
Subject Soacha E32519 entity
Predicate hasNeighbouringMunicipality P224 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: [Soacha, hasNeighbouringMunicipality, Mosquera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mosquera
Context triple: [Soacha, hasNeighbouringMunicipality, 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f8df00819086f34847e2170e12 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad4018f4c08190ad1994389b4e244c completed March 8, 2026, 9:23 a.m.
Created at: March 4, 2026, 7:26 p.m.