Triple

T21677462
Position Surface form Disambiguated ID Type / Status
Subject Next Plane Out E535009 entity
Predicate producer P490 FINISHED
Object Guy Roche 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: Guy Roche | Statement: [Next Plane Out, producer, Guy Roche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guy Roche
Context triple: [Next Plane Out, producer, Guy Roche]
  • A. Guy Roche chosen
    Guy Roche is a French-born American songwriter and record producer known for his work with major pop and R&B artists in the 1990s and 2000s.
  • B. Gerald Roche
    Gerald Roche is a scholar and linguist known for his research on the Monguor (Tu) language and the sociolinguistics of minority languages in China.
  • C. John Roche
    John Roche is a name shared by several notable individuals, including figures in politics, sports, and academia.
  • D. George Tierney
    George Tierney was a prominent late 18th- and early 19th-century British Whig politician known for his opposition to William Pitt the Younger and his role as a leading parliamentary critic of government policy.
  • E. Kevin Tighe
    Kevin Tighe is an American actor best known for his role as firefighter-paramedic Roy DeSoto on the television series "Emergency!" and for numerous character roles in film and television.
  • 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_69e0c46898008190aa618a4af55bd1ee completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef8a105b888190820b894d16c1ab77 completed April 27, 2026, 4:08 p.m.
Created at: April 16, 2026, 6:42 p.m.