Triple

T3674900
Position Surface form Disambiguated ID Type / Status
Subject CYYZ E77966 entity
Predicate servesCity P82 FINISHED
Object Mississauga E30860 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: Mississauga | Statement: [CYYZ, servesCity, Mississauga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mississauga
Context triple: [CYYZ, servesCity, Mississauga]
  • A. Mississauga chosen
    Mississauga is a large, diverse Canadian city in the Greater Toronto Area known for its major airport, corporate headquarters, and extensive suburban communities.
  • B. Caledon
    Caledon is a largely rural town in southern Ontario, Canada, known for its scenic landscapes and inclusion within the Greater Toronto Area.
  • C. Scugog
    Scugog is a township and lakeside community in south-central Ontario, Canada, known for its rural character, recreational opportunities around Lake Scugog, and proximity to the Greater Toronto Area.
  • D. Welland
    Welland is a city in the Niagara Region of southern Ontario, Canada, known for the Welland Canal that connects Lake Ontario and Lake Erie.
  • E. Orillia
    Orillia is a small city in central Ontario, Canada, known for its lakeside setting on Lake Couchiching and Lake Simcoe and its popular waterfront and cultural festivals.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4619cf08190a09a4a820c59cbc4 completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48856b7d481909d9cc32586d61d44 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.