Triple

T6262871
Position Surface form Disambiguated ID Type / Status
Subject Junín Region E140342 entity
Predicate hasProvince P285 FINISHED
Object Satipo Province E473595 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: Satipo Province | Statement: [Junín Region, hasProvince, Satipo Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Satipo Province
Context triple: [Junín Region, hasProvince, Satipo Province]
  • A. Satipo Province chosen
    Satipo Province is an administrative province located in Peru’s central Amazonian area, known for its tropical climate, indigenous communities, and rich biodiversity.
  • B. Huancané Province
    Huancané Province is an administrative division in southern Peru known for its high Andean geography and predominantly Aymara-speaking population.
  • C. Carabaya Province
    Carabaya Province is an administrative division in southeastern Peru known for its high Andean landscapes, mining activities, and location within the Puno Region near the border with Bolivia.
  • D. Marañón Province
    Marañón Province is an administrative province located in Peru’s central highland department of Huánuco, known for its Andean geography and rural communities.
  • E. Chanchamayo Province
    Chanchamayo Province is an agricultural and ecotourism-focused province in central Peru known for its coffee, citrus production, and lush high jungle landscapes.
  • 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_69c008c95c5c819084bd3dd56133d84d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06387fec0819095b47a37b9402aa9 completed March 22, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640a59c70819093a67d1a16fcef8b completed March 27, 2026, 8:32 a.m.
Created at: March 22, 2026, 4:25 p.m.