Triple

T23214721
Position Surface form Disambiguated ID Type / Status
Subject Lipstick, Powder and Paint E580702 entity
Predicate hasTrack P3284 FINISHED
Object Come See About Me 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: Come See About Me | Statement: [Lipstick, Powder and Paint, hasTrack, Come See About Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Come See About Me
Context triple: [Lipstick, Powder and Paint, hasTrack, Come See About Me]
  • A. Come See About Me chosen
    "Come See About Me" is a 1964 Motown hit single by The Supremes, known for its catchy melody, emotional lyrics, and success on the Billboard Hot 100 chart.
  • B. Come See Me
    "Come See Me" is a song best known as a 2016 R&B/hip-hop single by Canadian duo PARTYNEXTDOOR featuring Drake.
  • C. Come N See Me
    "Come N See Me" is a hip hop track by American rapper Ludacris from his album "Ludaversal."
  • D. You See Me
    "You See Me" is a song by the American indie rock band Camp.
  • E. See Me
    See Me is a romantic drama novel by Nicholas Sparks that follows the intertwined lives of a reformed troublemaker and an ambitious lawyer whose rekindled connection is threatened by a dangerous secret from the past.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f19163b9b88190a68fa6d08d37bdb7 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.