Triple

T10900721
Position Surface form Disambiguated ID Type / Status
Subject Videotron Centre E257431 entity
Predicate fundedBy P67 FINISHED
Object Quebecor E886800 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: Quebecor | Statement: [Videotron Centre, fundedBy, Quebecor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Quebecor
Context triple: [Videotron Centre, fundedBy, Quebecor]
  • A. Quebecor (Videotron) chosen
    Quebecor (Videotron) is a major Canadian telecommunications and media company best known for providing cable TV, internet, and wireless services, primarily in Quebec.
  • B. Rogers Media
    Rogers Media is a major Canadian media and communications company that owns and operates television and radio stations, sports media assets, and digital platforms.
  • C. Mountain Bell
    Mountain Bell was a regional Bell Operating Company that provided telephone service across several western U.S. states before being reorganized into US West.
  • D. Bell Media
    Bell Media is a major Canadian multimedia company that operates numerous television channels, radio stations, and digital platforms across the country.
  • E. Torstar Corporation
    Torstar Corporation is a Canadian media company best known as the publisher of the Toronto Star and other newspapers and digital media properties.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d761a2f02881908b70be6499dd8d98 completed April 9, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69e155306e9081909433522eeecf2b7d completed April 16, 2026, 9:31 p.m.
Created at: April 8, 2026, 9:22 p.m.