Triple

T1548930
Position Surface form Disambiguated ID Type / Status
Subject Girardot E33042 entity
Predicate isCapitalOf P204 FINISHED
Object Girardot Municipality E33042 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: Girardot Municipality | Statement: [Girardot, isCapitalOf, Girardot Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Girardot Municipality
Context triple: [Girardot, isCapitalOf, Girardot Municipality]
  • A. Girardot chosen
    Girardot is a Colombian city known as a major tourist and commercial center on the Magdalena River, popular for its warm climate and resort tourism.
  • B. Anapoima
    Anapoima is a warm-climate resort town and popular weekend getaway located in the Cundinamarca department of central Colombia.
  • C. Tunja
    Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
  • D. La Mesa, Cundinamarca
    La Mesa, Cundinamarca is a municipality and town in the Cundinamarca Department of Colombia, known for its mild climate and location on a plateau overlooking the Tequendama region.
  • E. Apartadó
    Apartadó is a municipality in Colombia’s Antioquia Department, known as an important agricultural and commercial center in the Urabá region, especially for banana production.
  • 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_69a885ee6db8819099502bc5ce8af881 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90856642c81909d88a679eb265b10 completed March 5, 2026, 4:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30a29ae88190ab1b2ca97b8ed09c completed March 8, 2026, 8:17 a.m.
Created at: March 4, 2026, 7:26 p.m.