Triple

T11750795
Position Surface form Disambiguated ID Type / Status
Subject Rogers Media E279397 entity
Predicate ownsBrand P1500 FINISHED
Object Sportsnet E54584 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: Sportsnet | Statement: [Rogers Media, ownsBrand, Sportsnet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sportsnet
Context triple: [Rogers Media, ownsBrand, Sportsnet]
  • A. Sportsnet chosen
    Sportsnet is a Canadian sports television network owned by Rogers Sports & Media that broadcasts a wide range of live sports, including Major League Baseball, NHL hockey, and other national and regional events.
  • B. Sportsnet World
    Sportsnet World is a Canadian specialty television channel focused on international soccer, rugby, and other global sports programming.
  • C. Sportsnet 590 The FAN
    Sportsnet 590 The FAN is a Toronto-based all-sports radio station known for its comprehensive coverage of local teams and major sporting events.
  • D. Réseau des sports
    Réseau des sports is a Canadian French-language specialty television channel focused on broadcasting sports events and related programming.
  • E. MSG Sportsnet
    MSG Sportsnet is a regional sports television channel in the New York metropolitan area that broadcasts live games and related programming for local professional and collegiate teams.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a508b0c4819082fbcc27d559ea2f completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a13550081909a26f57b30d68e03 completed April 28, 2026, 2:23 a.m.
Created at: April 8, 2026, 9:41 p.m.