Triple

T2505596
Position Surface form Disambiguated ID Type / Status
Subject Mississauga E52571 entity
Predicate hasNeighbour P5707 FINISHED
Object Oakville E39871 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: Oakville | Statement: [Mississauga, hasNeighbour, Oakville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oakville
Context triple: [Mississauga, hasNeighbour, Oakville]
  • A. Oakville, Ontario chosen
    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.
  • B. Brampton
    Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
  • C. Whitchurch-Stouffville, Ontario
    Whitchurch-Stouffville, Ontario is a rapidly growing town in the Greater Toronto Area known for its blend of suburban communities, historic village core, and surrounding agricultural and natural landscapes.
  • D. Vaughan
    Vaughan is a surname of Welsh origin that is notably associated with influential figures such as blues guitarist Stevie Ray Vaughan.
  • E. 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.
  • 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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1cec9f48190848b6129aa394ce4 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2248bcb68819095e52fea4cd5692c completed March 12, 2026, 2:27 a.m.
Created at: March 6, 2026, 9:46 p.m.