Triple

T842917
Position Surface form Disambiguated ID Type / Status
Subject Greater Toronto Area E18214 entity
Predicate contains P35 FINISHED
Object 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: Brampton | Statement: [Greater Toronto Area, contains, Brampton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brampton
Context triple: [Greater Toronto Area, contains, 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. Vaughan
    Vaughan is a rapidly growing suburban city in the Greater Toronto Area known for its diverse communities, shopping and entertainment complexes, and attractions like Canada’s Wonderland.
  • C. Oshawa
    Oshawa is a city in southern Ontario, Canada, known historically as a major automotive manufacturing center and part of the Greater Toronto Area.
  • D. 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.
  • E. Brantford
    Brantford is a city in southwestern Ontario, Canada, known as the hometown of hockey legend Wayne Gretzky and for its historic role in the development of telephone technology.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abe8a0bc81909b54af465e67be1f completed March 1, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac598e6ccc8190b0d75d36036f5e42 completed March 7, 2026, 4:59 p.m.
Created at: March 1, 2026, 7:38 p.m.