Triple

T6794568
Position Surface form Disambiguated ID Type / Status
Subject Breslau, Ontario E156020 entity
Predicate censusDivision P10770 FINISHED
Object 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: Waterloo | Statement: [Breslau, Ontario, censusDivision, Waterloo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterloo
Context triple: [Breslau, Ontario, censusDivision, Waterloo]
  • A. 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.
  • B. Waterloo
    Waterloo was the original name of the settlement that later became the city of Austin, the capital of Texas.
  • C. 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.
  • D. 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.
  • E. Waterloo
    Waterloo is a coastal town in the Metropolitan Borough of Sefton, Merseyside, England, known for its stretch of beach and proximity to Liverpool.
  • 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_69c6881844448190a65822d9b39d7f88 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2c59648819081736d27d52d957f completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a90dfb081909120e8502b26a88b completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:15 p.m.