Triple

T20907887
Position Surface form Disambiguated ID Type / Status
Subject Fort William Municipal Airport E514852 entity
Predicate pushpinMap P1987 FINISHED
Object Canada Ontario 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: Canada Ontario | Statement: [Fort William Municipal Airport, pushpinMap, Canada Ontario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canada Ontario
Context triple: [Fort William Municipal Airport, pushpinMap, Canada Ontario]
  • A. Ontario
    Ontario is a city in southwestern San Bernardino County, California, known as a major logistics and transportation hub anchored by Ontario International Airport and extensive freeway and rail connections.
  • B. Ontario chosen
    Ontario is Canada’s most populous province, home to the nation’s capital Ottawa and its largest city Toronto, and a major economic and cultural hub.
  • C. Ontario
    Ontario is a small village in Belize’s Cayo District, known as a rural community along the George Price Highway west of the capital, Belmopan.
  • D. British Columbia
    British Columbia is a western Canadian province known for its Pacific coastline, mountainous landscapes, and major cities such as Vancouver and Victoria.
  • E. Canada East
    Canada East was the historical name for the predominantly French-speaking region that later became the province of Quebec in Canada.
  • 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_69e0b4f8a1108190bce3d31331290ced completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6e900ee7881909ab1046b40dca486 completed April 21, 2026, 3:03 a.m.
Created at: April 16, 2026, 12:47 p.m.