Triple

T19118161
Position Surface form Disambiguated ID Type / Status
Subject Darlene Hunt E467961 entity
Predicate employer P7 FINISHED
Object Showtime 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: Showtime | Statement: [Darlene Hunt, employer, Showtime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Showtime
Context triple: [Darlene Hunt, employer, Showtime]
  • A. Showtime chosen
    Showtime is an American premium cable and streaming network known for its original, often edgy series, films, and sports programming.
  • B. Cinemax
    Cinemax is an American premium cable and satellite television network known for airing feature films, original series, and late-night programming.
  • C. HBO
    HBO is a premium American television and streaming network known for producing influential, high-quality original series, films, and documentaries such as "The Sopranos," "Game of Thrones," and "Succession."
  • D. HBO
    HBO is the Dutch sector of universities of applied sciences that focuses on professionally oriented higher education and practical training.
  • E. Epix
    Epix was a premium American cable and streaming television network known for airing recent Hollywood films, original series, and specials before being rebranded as MGM+.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3c756a88190942930e6ae7242a7 completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.