Triple

T20609420
Position Surface form Disambiguated ID Type / Status
Subject She's So Unusual E506403 entity
Predicate single P3283 FINISHED
Object Money Changes Everything 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: Money Changes Everything | Statement: [She's So Unusual, single, Money Changes Everything]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Money Changes Everything
Context triple: [She's So Unusual, single, Money Changes Everything]
  • A. Money Changes Everything chosen
    "Money Changes Everything" is a rock/new wave song best known for Cyndi Lauper’s energetic 1984 cover, which became one of her notable hits.
  • B. The Money
    "The Money" is a popular Afrobeats song by Nigerian producer and songwriter Kiddominant.
  • C. The Moneychangers
    The Moneychangers is a 1975 novel by Arthur Hailey that offers a dramatic, behind-the-scenes look at the inner workings, power struggles, and ethical dilemmas within a large American bank.
  • D. The Riches
    The Riches is a darkly comedic American television drama series about a family of Irish Traveller con artists who assume the identities of a wealthy suburban couple.
  • E. Where the Money Is
    Where the Money Is is a 2000 crime-comedy film starring Paul Newman as an aging bank robber who plots one last heist with a bored nurse played by Linda Fiorentino.
  • 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_69e0b4bb2b4081908fa4a72444120f35 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aad5e53c8190b0add34ce9b31d57 completed April 20, 2026, 10:38 p.m.
Created at: April 16, 2026, 11:41 a.m.