Triple

T14103568
Position Surface form Disambiguated ID Type / Status
Subject Brown Sugar E339443 entity
Predicate hasPart P35 FINISHED
Object Smooth E143568 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: Smooth | Statement: [Brown Sugar, hasPart, Smooth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Smooth
Context triple: [Brown Sugar, hasPart, Smooth]
  • A. Smooth chosen
    "Smooth" is a Grammy-winning Latin rock and pop song by Santana featuring Rob Thomas, renowned for its infectious groove and massive late-1990s chart success.
  • B. E Smooth
    E Smooth is the professional alias of Erik "E Smooth" Hicks, known for his work in the music and entertainment industry.
  • C. Smooth Character
    Smooth Character is the nickname of Old Joe, suggesting a persona known for charm, ease, and a laid-back, confident demeanor.
  • D. Smooth Operator
    "Smooth Operator" is a smooth jazz-influenced pop song by Sade, known for its sultry vocals and sophisticated, late-night atmosphere that helped define the band's signature sound in the 1980s.
  • E. Smooth Talk
    Smooth Talk is a 1985 coming-of-age drama film, loosely based on a Joyce Carol Oates short story, about a teenage girl’s unsettling encounter with an older man.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5fbd02888190bf07fd6d8769b61c completed April 14, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0b2ade08190a56e9ecf659f83b9 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.