Triple

T6304807
Position Surface form Disambiguated ID Type / Status
Subject Gardiner Expressway E141347 entity
Predicate connectsTo P845 FINISHED
Object Downtown Toronto E18465 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: Downtown Toronto | Statement: [Gardiner Expressway, connectsTo, Downtown Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Downtown Toronto
Context triple: [Gardiner Expressway, connectsTo, Downtown Toronto]
  • A. Downtown Toronto chosen
    Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
  • B. Midtown Toronto
    Midtown Toronto is a central district of Toronto known for its mix of residential neighborhoods, historic landmarks, and vibrant commercial areas.
  • C. Toronto
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • 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. Toronto section
    The Toronto section is an urban and suburban stretch of Ontario’s Bruce Trail that follows the Niagara Escarpment through and around 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0645f26a881909d5746151c0843cc completed March 22, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e44527488190b3d605e917c8dfb2 completed March 27, 2026, 1:58 a.m.
Created at: March 22, 2026, 4:28 p.m.