Triple

T22001821
Position Surface form Disambiguated ID Type / Status
Subject Louise Frogley E543343 entity
Predicate workedOn P3 FINISHED
Object Money Monster 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 Monster | Statement: [Louise Frogley, workedOn, Money Monster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Money Monster
Context triple: [Louise Frogley, workedOn, Money Monster]
  • A. Money Monster chosen
    Money Monster is a 2016 American thriller film about a live financial TV show taken hostage on air, blending media satire with real-time suspense.
  • B. Money Mania
    Money Mania is a work that explores themes of speculative financial frenzy and irrational economic behavior, closely associated with the classic study of mass financial delusions.
  • C. Moneybags
    Moneybags is a recurring, money-obsessed bear character in the Spyro the Dragon video game series who charges the player gems to unlock paths, abilities, and characters.
  • D. Tons of Money
    Tons of Money is a classic British farce, originally a 1922 stage play, known for its rapid-fire misunderstandings and mistaken identities surrounding an impoverished inventor’s inheritance scheme.
  • E. All Money In
    All Money In is an independent record label founded by rapper and entrepreneur Nipsey Hussle to release his music and support artists from his community.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276ae4e0819097bf1b978451f776 completed April 28, 2026, 9:32 p.m.
Created at: April 16, 2026, 8:20 p.m.