Triple

T378085
Position Surface form Disambiguated ID Type / Status
Subject Quito E8614 entity
Predicate isSeatOf P62 FINISHED
Object Pichincha Province E47502 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: Pichincha Province | Statement: [Quito, isSeatOf, Pichincha Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pichincha Province
Context triple: [Quito, isSeatOf, Pichincha Province]
  • A. Pichincha Province chosen
    Pichincha Province is an Andean region in north-central Ecuador known for its capital city Quito and the active stratovolcano Pichincha.
  • B. Boyacá Department
    Boyacá Department is a region in central Colombia known for its Andean landscapes, colonial towns like Villa de Leyva, and its historical role in the country’s independence.
  • C. Huila Department
    Huila Department is an administrative region in southwestern Colombia known for its coffee production, the Magdalena River’s upper valley, and the Tatacoa Desert.
  • D. Limarí Province
    Limarí Province is an administrative division in north-central Chile known for its semi-arid climate, agriculture, and pisco-producing valleys.
  • E. Tolima Department
    Tolima Department is an administrative region in central Colombia known for its Andean landscapes, agricultural production, and capital city Ibagué.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec2974988190a1d6316cbb5159c8 completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3fafe091881908fdf8ddbb6b8a7e6 completed March 1, 2026, 8:38 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.