Triple

T4867006
Position Surface form Disambiguated ID Type / Status
Subject I Want You E108994 entity
Predicate hasNotableCoverVersionBy P11142 FINISHED
Object Michael Bolton E266843 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: Michael Bolton | Statement: [I Want You, hasNotableCoverVersionBy, Michael Bolton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Bolton
Context triple: [I Want You, hasNotableCoverVersionBy, Michael Bolton]
  • A. Michael Bolton chosen
    Michael Bolton is an American singer and songwriter known for his powerful, soulful ballads and successful pop and adult contemporary hits, especially in the late 1980s and early 1990s.
  • B. Brian Aldridge
    Brian Aldridge is a fictional character from the long-running BBC Radio 4 soap opera "The Archers," known as a wealthy and sometimes controversial farmer and landowner in the series.
  • C. Mick Rogers
    Mick Rogers is an Australian former professional road cyclist known for his time-trialling strength and multiple world championship titles in the team time trial.
  • D. Tom Bell
    Tom Bell was an American football official best known for serving as the referee in Super Bowl III.
  • E. Tom Bell
    Tom Bell was a British character actor known for his intense, gritty performances in film and television from the 1960s onward.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d7bb0b88190bbc24498619910fc completed March 20, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67e5d96c8190b2a509d9fb81211a completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:26 p.m.