Triple

T23507404
Position Surface form Disambiguated ID Type / Status
Subject Sheryl Lee E572319 entity
Predicate notableWork P4 FINISHED
Object Dirty Sexy Money 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: Dirty Sexy Money | Statement: [Sheryl Lee, notableWork, Dirty Sexy Money]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dirty Sexy Money
Context triple: [Sheryl Lee, notableWork, Dirty Sexy Money]
  • A. Dirty Sexy Money chosen
    Dirty Sexy Money is an American television drama series that follows a lawyer who becomes entangled in the scandals and secrets of a wealthy New York family.
  • B. Dirty Money
    "Dirty Money" is a track by rapper Pusha T from his critically acclaimed 2006 album *Hell Hath No Fury*.
  • C. Dirty Money
    "Dirty Money" is a song by the Southern hip hop duo UGK, known for its gritty depiction of street life and hustling.
  • D. Dirty Money
    Dirty Money is an American hip hop and R&B girl group formed by Sean "Diddy" Combs, known for blending soulful vocals with contemporary rap and dance production.
  • E. Dirty Money
    Dirty Money is a documentary television series that investigates corporate greed, corruption, and financial crime through in-depth case studies.
  • 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_69e245b5e4208190bac8a6509867e394 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a901c9908190a781e79fe8b96743 completed April 29, 2026, 6:45 a.m.
Created at: April 17, 2026, 6:07 p.m.