Triple

T5914231
Position Surface form Disambiguated ID Type / Status
Subject Cuts E131537 entity
Predicate producerCompany P25234 FINISHED
Object Big Ticket Television E208248 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: Big Ticket Television | Statement: [Cuts, producerCompany, Big Ticket Television]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Big Ticket Television
Context triple: [Cuts, producerCompany, Big Ticket Television]
  • A. Big Ticket Television chosen
    Big Ticket Television is an American television production company known for producing popular sitcoms and syndicated series in the 1990s and 2000s.
  • B. The Ticket
    The Ticket is a 2016 American drama film about a blind man who regains his sight and becomes consumed by ambition, starring Dan Stevens and Kerry Bishé.
  • C. The Big Ticket
    The Big Ticket is the famous nickname of NBA Hall of Famer Kevin Garnett, known for his intense competitiveness and all-around dominance on the basketball court.
  • D. Raseedi Ticket
    Raseedi Ticket is an autobiographical work by renowned Punjabi writer Amrita Pritam, reflecting on her personal life, relationships, and literary journey.
  • E. Imagine Television
    Imagine Television is the television production division of Imagine Entertainment, known for developing and producing a wide range of scripted and unscripted TV series.
  • 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_69c008593a44819081a07ae0efe6c574 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c049fdb3e08190a72337ab4f48bc8e completed March 22, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c02430bc8190a63b91b6dbdbc9f2 completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 3:59 p.m.