Triple

T21042157
Position Surface form Disambiguated ID Type / Status
Subject My Life with John Thaw E518352 entity
Predicate mainSubject P3 FINISHED
Object John Thaw 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: John Thaw | Statement: [My Life with John Thaw, mainSubject, John Thaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Thaw
Context triple: [My Life with John Thaw, mainSubject, John Thaw]
  • A. John Thaw chosen
    John Thaw was a renowned English actor best known for his iconic role as Inspector Morse in the long-running British television series of the same name.
  • B. John Nettles
    John Nettles is a British actor best known for starring as Detective Chief Inspector Tom Barnaby in the long-running television crime drama "Midsomer Murders."
  • C. Frazer Hines
    Frazer Hines is a British actor best known for his long-running role as companion Jamie McCrimmon in the classic science fiction television series Doctor Who.
  • D. Dennis Waterman
    Dennis Waterman was an English actor and singer best known for his tough-guy roles in British television dramas such as The Sweeney, Minder, and New Tricks.
  • E. Neil Cross
    Neil Cross is a British novelist and screenwriter best known for creating the acclaimed crime drama television series "Luther."
  • 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_69e0b50438e08190917e2538bb8bc034 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fcf0b27881909d1c5b58be387a74 completed April 21, 2026, 4:28 a.m.
Created at: April 16, 2026, 2:15 p.m.