Triple

T9529550
Position Surface form Disambiguated ID Type / Status
Subject Pop E229850 entity
Predicate formerName P65 FINISHED
Object TVGN E98192 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: TVGN | Statement: [Pop, formerName, TVGN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TVGN
Context triple: [Pop, formerName, TVGN]
  • A. WGN America chosen
    WGN America is a U.S.-based cable television network known for airing syndicated series, movies, and original programming to a national audience.
  • B. TV One
    TV One is an American cable television network that primarily targets African American audiences with a mix of original series, movies, and lifestyle programming.
  • C. TV Land
    TV Land is an American cable television network known for airing classic television series and original sitcoms aimed primarily at adult audiences.
  • D. GTV
    GTV is a Japanese television network that has broadcast popular anime series such as Demon Slayer: Kimetsu no Yaiba.
  • E. TNT network
    TNT network is an American cable television channel known for airing drama series, sports coverage, and feature films.
  • 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_69ca8479934c81908006d0e6e970ae05 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98b1b93481909812245ac14e4988 completed April 1, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69d14c38a3848190ab3561f70497c9eb completed April 4, 2026, 5:36 p.m.
Created at: March 30, 2026, 8 p.m.