Triple

T1038625
Position Surface form Disambiguated ID Type / Status
Subject Golden Horseshoe E22419 entity
Predicate includes P1393 FINISHED
Object City of Brampton E30924 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: City of Brampton | Statement: [Golden Horseshoe, includes, City of Brampton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Brampton
Context triple: [Golden Horseshoe, includes, City of Brampton]
  • A. Brampton chosen
    Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
  • B. Oakville, Ontario
    Oakville, Ontario is a suburban town on Lake Ontario in the Greater Toronto Area, known for its affluent neighborhoods, harbors, and vibrant arts and cultural scene.
  • C. North York
    North York is a major district in the north end of Toronto, Ontario, known for its dense urban development, shopping centers, and mixed residential and commercial areas.
  • D. Richmond Hill, Ontario
    Richmond Hill, Ontario is a suburban city in the Greater Toronto Area known for its diverse population, strong economy, and rapidly growing residential communities.
  • E. Caledon
    Caledon is a largely rural town in southern Ontario, Canada, known for its scenic landscapes and inclusion within the Greater Toronto Area.
  • 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b82b3ef08190bcd24845b4418d47 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce55b5748190b54b8205a735ae89 completed March 8, 2026, 1:18 a.m.
Created at: March 1, 2026, 7:41 p.m.