Triple

T12845187
Position Surface form Disambiguated ID Type / Status
Subject Lisa Wilkinson E307155 entity
Predicate employer P7 FINISHED
Object Network 10 E59113 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: Network 10 | Statement: [Lisa Wilkinson, employer, Network 10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Network 10
Context triple: [Lisa Wilkinson, employer, Network 10]
  • A. 10 Network Holdings
    10 Network Holdings is a media company that owns and operates the 10 Play streaming platform associated with Australia’s Network 10 television brand.
  • B. Network Ten chosen
    Network Ten is a major Australian commercial television network known for broadcasting popular entertainment, news, and sports programming nationwide.
  • C. TPG network
    The TPG network is the public transportation system serving Geneva, Switzerland, operated by Transports Publics Genevois and encompassing trams, buses, and trolleybuses across the city and surrounding areas.
  • D. Optus
    Optus is a major Australian telecommunications company providing mobile, internet, and related communication services nationwide.
  • E. Nine Network
    Nine Network is a major Australian commercial television network known for broadcasting popular news, sports, and entertainment programming nationwide.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff3a7208190b93f6292ed5efc07 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5ed774881909d2df630820e5f21 completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 5:36 p.m.