Triple

T11025745
Position Surface form Disambiguated ID Type / Status
Subject Nevado de Santa Isabel E260611 entity
Predicate nearbyCity P350 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: [Nevado de Santa Isabel, nearbyCity, Manizales]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manizales
Context triple: [Nevado de Santa Isabel, nearbyCity, 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797d0cd988190a7b21d7bdc3109ce completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e37523f8548190ad40fa76660232a8 completed April 18, 2026, 12:12 p.m.
Created at: April 8, 2026, 9:25 p.m.