Triple

T6480122
Position Surface form Disambiguated ID Type / Status
Subject Ontario Heritage Trust E146169 entity
Predicate regionServed P82 FINISHED
Object Ontario E3554 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: Ontario | Statement: [Ontario Heritage Trust, regionServed, Ontario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ontario
Context triple: [Ontario Heritage Trust, regionServed, Ontario]
  • A. 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.
  • B. 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.
  • C. British Columbia
    British Columbia is a western Canadian province known for its Pacific coastline, mountainous landscapes, and major cities such as Vancouver and Victoria.
  • D. Manitoba
    Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
  • E. Saskatchewan
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a4e764c819086828bb841f588e0 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65394d8b481909868faf79f3d2383 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:51 p.m.