Triple

T6689669
Position Surface form Disambiguated ID Type / Status
Subject Elgin Theatre E152591 entity
Predicate neighbourhood P988 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: [Elgin Theatre, neighbourhood, Downtown Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Downtown Toronto
Context triple: [Elgin Theatre, neighbourhood, 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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b15149408190ac679d037d87cba7 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f78f667c81908c2de74009c8e073 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:04 p.m.