Triple

T21758669
Position Surface form Disambiguated ID Type / Status
Subject Surquillo District E537104 entity
Predicate capital P234 FINISHED
Object Surquillo NE NERFINISHED

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: Surquillo | Statement: [Surquillo District, capital, Surquillo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surquillo
Context triple: [Surquillo District, capital, Surquillo]
  • A. Surquillo chosen
    Surquillo is a densely populated urban district of Lima, Peru, known for its residential neighborhoods, markets, and proximity to the upscale area of Miraflores.
  • B. Avanceña
    Avanceña is a Filipino surname associated with several notable figures in the Philippines, including public servants and cultural personalities.
  • C. San Pablo del Monte
    San Pablo del Monte is a city in the Mexican state of Tlaxcala that forms part of the greater Puebla metropolitan region and is known for its traditional crafts and growing urban development.
  • D. Alvear
    Alvear is a town in the Rosario Department of Santa Fe Province, Argentina, functioning as part of the greater Rosario metropolitan area.
  • E. Alvear
    Alvear is a small town in the San Martín Department of Corrientes Province in northeastern Argentina, known for its riverside setting along the Uruguay River and regional livestock and agricultural activities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46eab808190b848242d63a17c47 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01d902c9881908051904e44a136af completed April 28, 2026, 2:38 a.m.
Created at: April 16, 2026, 6:50 p.m.