Triple

T1408968
Position Surface form Disambiguated ID Type / Status
Subject Till Death Us Do Part E31759 entity
Predicate workLocationOf P1527 FINISHED
Object Johnny Speight E217631 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: Johnny Speight | Statement: [Till Death Us Do Part, workLocationOf, Johnny Speight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johnny Speight
Context triple: [Till Death Us Do Part, workLocationOf, Johnny Speight]
  • A. Johnny Speight chosen
    Johnny Speight was a British television scriptwriter best known for his sharp, socially satirical comedy and creation of controversial, working-class characters.
  • B. Keith Foulke
    Keith Foulke is a former Major League Baseball relief pitcher best known as the Boston Red Sox closer who played a pivotal role in their 2004 World Series championship run.
  • C. Eddie Leslie
    Eddie Leslie was a British screenwriter and actor known for his work on mid-20th-century comedy films.
  • D. Fred Barker
    Fred Barker was an American gangster and member of the notorious Barker–Karpis gang during the early 20th-century crime wave in the United States.
  • E. Jon Shirley
    Jon Shirley is an American businessman and former Microsoft executive known for helping lead the company’s early growth and for his philanthropy in the arts and education.
  • 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_69a49918e1f88190ba610f9dc8114578 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c3c10f44819085e1c4601423740d completed March 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fae5aa08190b6aa50b543a175b8 completed March 9, 2026, 1:17 a.m.
Created at: March 1, 2026, 7:59 p.m.