Triple

T13962743
Position Surface form Disambiguated ID Type / Status
Subject Sostiene Pereira E335837 entity
Predicate mainCharacter P1183 FINISHED
Object Pereira E929530 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: Pereira | Statement: [Sostiene Pereira, mainCharacter, Pereira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pereira
Context triple: [Sostiene Pereira, mainCharacter, Pereira]
  • A. Pereira chosen
    Pereira is a common Portuguese-language surname widely found in Brazil, Portugal, and other Lusophone communities.
  • B. 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.
  • C. Manizales
    Manizales is a mountainous Colombian city known for its coffee production, cool climate, and location in the central Andes.
  • D. Tunja
    Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
  • E. 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.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7c73d48190b8e02971b5a8ed5f completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac8e47d48190a1d5e841810fe50c completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:18 p.m.