Triple

T7774820
Position Surface form Disambiguated ID Type / Status
Subject Paisas E179164 entity
Predicate majorCity P316 FINISHED
Object Manizales E208912 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: Manizales | Statement: [Paisas, majorCity, Manizales]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manizales
Context triple: [Paisas, majorCity, Manizales]
  • A. Manizales chosen
    Manizales is a mountainous Colombian city known for its coffee production, cool climate, and location in the central Andes.
  • B. Tunja
    Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
  • C. Bucaramanga
    Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
  • D. Popayán
    Popayán is a historic colonial city in southwestern Colombia, renowned for its whitewashed architecture, rich religious traditions, and prominent Holy Week celebrations.
  • E. Pereira
    Pereira is a major Colombian city known as the capital of the Risaralda department and an important economic and cultural center in the country's coffee-growing region.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c7046331e0819080ec1a5c23c27cd7 completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c968cfdb1081908961f825b616a708 completed March 29, 2026, 6 p.m.
Created at: March 27, 2026, 4:11 p.m.