Triple

T17897042
Position Surface form Disambiguated ID Type / Status
Subject Spectrum Mobile E447456 entity
Predicate usesNetworkOf P30353 FINISHED
Object Verizon Wireless NE NERFINISHED

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: Verizon Wireless | Statement: [Spectrum Mobile, usesNetworkOf, Verizon Wireless]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Verizon Wireless
Context triple: [Spectrum Mobile, usesNetworkOf, Verizon Wireless]
  • A. Verizon chosen
    Verizon is a major American telecommunications company providing wireless, internet, and related communication services across the United States and globally.
  • B. Rogers Wireless
    Rogers Wireless is one of Canada’s largest mobile network operators, providing nationwide wireless voice, data, and related telecommunications services.
  • C. T-Mobile US
    T-Mobile US is a major American wireless network operator known for its nationwide mobile phone services and aggressive “Un-carrier” marketing strategy.
  • D. AT&T
    AT&T is a major American telecommunications conglomerate known for providing wireless, internet, and media services nationwide.
  • E. U.S. Cellular
    U.S. Cellular is a regional American wireless telecommunications provider offering mobile phone and data services, primarily in the Midwest and rural areas of the United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d8045748190a4e8c4684439a96b completed April 19, 2026, 9:16 a.m.
Created at: April 10, 2026, 10:19 a.m.