Triple

T14756520
Position Surface form Disambiguated ID Type / Status
Subject Ron Newman E346742 entity
Predicate playedFor P2170 FINISHED
Object Toronto City E1525 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: Toronto City | Statement: [Ron Newman, playedFor, Toronto City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto City
Context triple: [Ron Newman, playedFor, Toronto City]
  • A. Toronto chosen
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • B. Toronto Centre
    Toronto Centre is a densely populated federal electoral district in downtown Toronto, Ontario, known for its diverse communities and significant political prominence.
  • C. Downtown Toronto
    Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
  • D. Metropolitan Toronto
    Metropolitan Toronto was a former regional government in Ontario, Canada that encompassed the city of Toronto and its surrounding municipalities before their amalgamation into a single city in 1998.
  • E. Wellington, Ontario
    Wellington, Ontario is a small lakeside community in Prince Edward County known for its wineries, beaches, and vibrant arts and culinary scene.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7ef0fd48190bd4a8af128ef274c completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cea5d348190a84970da131292ee completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:30 a.m.