Triple

T19851100
Position Surface form Disambiguated ID Type / Status
Subject Thanks for the Dance E476992 entity
Predicate hasContributor P4244 FINISHED
Object Daniel Lanois 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: Daniel Lanois | Statement: [Thanks for the Dance, hasContributor, Daniel Lanois]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Lanois
Context triple: [Thanks for the Dance, hasContributor, 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 (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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65868ccbc8190b879e9763706c1c5 completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.