Triple
T14877659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harley Peyton |
E349908
|
entity |
| Predicate | workOn |
P30363
|
FINISHED |
| Object | Friends with Money |
E741100
|
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: Friends with Money | Statement: [Harley Peyton, workOn, Friends with Money]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Friends with Money Context triple: [Harley Peyton, workOn, Friends with Money]
-
A.
Friends with Money
chosen
Friends with Money is a 2006 ensemble dramedy film written and directed by Nicole Holofcener that explores the intersecting lives, class anxieties, and relationships of four women in Los Angeles.
-
B.
Dirty Money
"Dirty Money" is a song by the Southern hip hop duo UGK, known for its gritty depiction of street life and hustling.
-
C.
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.
-
D.
Dirty Money
"Dirty Money" is a track by rapper Pusha T from his critically acclaimed 2006 album *Hell Hath No Fury*.
-
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 (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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e4e4448190a8796573bc6d1069 |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b54ad7c819082575245da07e358 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:55 a.m.