Triple

T5863893
Position Surface form Disambiguated ID Type / Status
Subject Get On Your Boots E130339 entity
Predicate producer P490 FINISHED
Object Daniel Lanois E124296 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: Daniel Lanois | Statement: [Get On Your Boots, producer, Daniel Lanois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Lanois
Context triple: [Get On Your Boots, producer, Daniel Lanois]
  • A. Daniel Lanois chosen
    Daniel Lanois is a Canadian record producer, musician, and songwriter renowned for his atmospheric, textural production work with artists such as U2, Bob Dylan, and Peter Gabriel.
  • B. Mitchell Froom
    Mitchell Froom is an American record producer and musician known for his innovative, atmospheric work with artists such as Crowded House, Suzanne Vega, and Los Lobos.
  • C. Butch Vig
    Butch Vig is an American record producer and musician best known for producing Nirvana's landmark album "Nevermind" and as the drummer for the alternative rock band Garbage.
  • D. David Shaw
    David Shaw is an American football coach best known for his successful tenure as head coach of Stanford University's football program in the 2010s.
  • E. David Shaw
    David Shaw was an American screenwriter known for his work in mid-20th-century film and television.
  • 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_69c0084f3bb08190a7720f55f7aa4252 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035bdd698819089ffe5256df492aa completed March 22, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c669d13b788190a6568d2d080ebdc6 completed March 27, 2026, 11:28 a.m.
Created at: March 22, 2026, 3:56 p.m.