Triple

T13400456
Position Surface form Disambiguated ID Type / Status
Subject Toronto PATH system E319812 entity
Predicate maintainedBy P86 FINISHED
Object City of Toronto 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: City of Toronto | Statement: [Toronto PATH system, maintainedBy, City of Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Toronto
Context triple: [Toronto PATH system, maintainedBy, City of Toronto]
  • A. 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.
  • B. Toronto chosen
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • 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. Municipality of Toronto
    The Municipality of Toronto is Canada’s largest city and economic hub, located in the province of Ontario on the northwestern shore of Lake Ontario.
  • E. City of Ontario
    The City of Ontario is a major suburban city in southwestern San Bernardino County, California, known for its international airport, logistics hubs, and role as an Inland Empire commercial center.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbae47e99081909d8b5dba97a11988 completed April 12, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d84d19081909f564c90b50fda60 completed May 3, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:34 p.m.