Triple

T7993953
Position Surface form Disambiguated ID Type / Status
Subject Ubaté Province E186076 entity
Predicate capital P234 FINISHED
Object Ubaté E33390 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: Ubaté | Statement: [Ubaté Province, capital, Ubaté]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ubaté
Context triple: [Ubaté Province, capital, Ubaté]
  • A. Ubaté chosen
    Ubaté is a town and municipality in central Colombia known for its dairy production and colonial-era architecture.
  • B. Girardota
    Girardota is a municipality in the Antioquia Department of Colombia, located in the northern part of the Aburrá Valley metropolitan area near Medellín.
  • C. Colomars
    Colomars is a small commune in southeastern France situated in the hills northwest of Nice, known for its scenic Mediterranean landscape and proximity to the French Riviera.
  • D. Sabaneta
    Sabaneta is a small but densely populated municipality in the Medellín metropolitan area of Colombia’s Aburrá Valley, known for its rapid urban growth and residential character.
  • E. Ciudad Ojeda
    Ciudad Ojeda is an oil-industry city in northwestern Venezuela, located on the eastern shore of Lake Maracaibo in Zulia state.
  • 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_69ca829c6c308190ab05b43d234c52b2 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c73ba388190bcedc29fbdd22f3c completed March 31, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe105d400819096ba271416bb24e7 completed March 31, 2026, 2:58 p.m.
Created at: March 30, 2026, 5:16 p.m.