Triple

T891373
Position Surface form Disambiguated ID Type / Status
Subject Larcomar E19245 entity
Predicate locatedIn P40 FINISHED
Object Miraflores District E26173 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: Miraflores District | Statement: [Larcomar, locatedIn, Miraflores District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miraflores District
Context triple: [Larcomar, locatedIn, Miraflores District]
  • A. Santiago de Surco
    Santiago de Surco is a large, predominantly residential and commercial district in southern Lima, Peru, known for its middle- to upper-class neighborhoods, shopping centers, and educational institutions.
  • B. San Miguel district, Lima
    San Miguel district, Lima is a coastal urban district of Peru’s capital city known for its residential areas, shopping centers, and educational institutions.
  • C. Cercado de Lima
    Cercado de Lima is the historic central district of Lima, Peru, encompassing the city’s colonial core, main government buildings, and numerous cultural landmarks.
  • D. Chorrillos
    Chorrillos is a coastal district in southern Lima, Peru, known for its beaches, fishing heritage, and role as a popular seaside resort area.
  • E. Miraflores chosen
    Miraflores is an upscale coastal district of Lima, Peru, known for its shopping, dining, nightlife, and cliffside views over the Pacific Ocean.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad019e448190ab991e85dc6d7708 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac762e945c8190a4716a2115689b20 completed March 7, 2026, 7:02 p.m.
Created at: March 1, 2026, 7:39 p.m.