Triple

T14560049
Position Surface form Disambiguated ID Type / Status
Subject Static Major E341642 entity
Predicate notableWork P4 FINISHED
Object One in a Million E341634 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: One in a Million | Statement: [Static Major, notableWork, One in a Million]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: One in a Million
Context triple: [Static Major, notableWork, One in a Million]
  • A. One in a Million
    "One in a Million" is an R&B song by American singer-songwriter Ne-Yo, known for its smooth production and romantic lyrics.
  • B. One in a Million
    "One in a Million" is a country song by American singer Johnny Lee, best known for its romantic theme and traditional country style.
  • C. One in a Million chosen
    "One in a Million" is Aaliyah's influential 1996 R&B album that helped redefine the genre with its innovative production and smooth, futuristic sound.
  • D. Two in a Million
    "Two in a Million" is a pop ballad by British group S Club 7, known for its romantic lyrics and smooth, melodic style that helped establish the band's late-1990s chart success.
  • E. A Million to One
    "A Million to One" is a doo-wop ballad best known for its romantic, pleading lyrics and classic 1960s vocal harmony style.
  • 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_69d822db9c8481908213ceb39585f792 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb389d0f48190a1d9d69456d1cbe1 completed April 14, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde16830c0819090a97b073c8e642d completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:23 a.m.