Triple

T9011507
Position Surface form Disambiguated ID Type / Status
Subject Greater Golden Horseshoe E215483 entity
Predicate contains P35 FINISHED
Object City of Waterloo E192540 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 Waterloo | Statement: [Greater Golden Horseshoe, contains, City of Waterloo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: City of Waterloo
Context triple: [Greater Golden Horseshoe, contains, City of Waterloo]
  • A. Waterloo chosen
    Waterloo is a mid-sized Canadian city in southwestern Ontario known for its universities, tech industry, and role within the Kitchener–Waterloo metropolitan area.
  • B. Waterloo
    Waterloo is a town in present-day Belgium best known as the site of Napoleon Bonaparte’s decisive defeat in 1815, which ended the Napoleonic Wars and reshaped European politics.
  • C. Waterloo
    Waterloo is a coastal town in the Metropolitan Borough of Sefton, Merseyside, England, known for its stretch of beach and proximity to Liverpool.
  • D. Waterloo
    Waterloo is a city in northeastern Iowa that serves as a regional hub for industry, transportation, and education along the Cedar River.
  • E. Waterloo
    Waterloo is a major district in central London known for its busy railway station, cultural venues like the Southbank Centre, and proximity to landmarks such as the London Eye and the River Thames.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69f846f88190af65dfcf8bdd936a completed April 1, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9dca848190952427bb5712081f completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:06 p.m.