Triple

T1569867
Position Surface form Disambiguated ID Type / Status
Subject Antioquia Department E33513 entity
Predicate containsCity P294 FINISHED
Object Apartadó E135529 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: Apartadó | Statement: [Antioquia Department, containsCity, Apartadó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apartadó
Context triple: [Antioquia Department, containsCity, Apartadó]
  • A. Apartadó chosen
    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.
  • B. 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.
  • C. Tunja
    Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
  • 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. Manizales
    Manizales is a mountainous Colombian city known for its coffee production, cool climate, and location in the central Andes.
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908b67304819081ad555000e51197 completed March 5, 2026, 4:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6518e07081909c34a363d7ac0f25 completed March 9, 2026, 6:13 a.m.
Created at: March 4, 2026, 7:27 p.m.