Triple
T36085120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OnlyFans |
E1043753
|
entity |
| Predicate | revenueModelDetail |
P100104
|
FINISHED |
| Object | platform takes percentage of creator earnings |
—
|
LITERAL 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: platform takes percentage of creator earnings | Statement: [OnlyFans, revenueModelDetail, platform takes percentage of creator earnings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revenueModelDetail Context triple: [OnlyFans, revenueModelDetail, platform takes percentage of creator earnings]
-
A.
usesRevenueModel
Indicates that one entity applies or operates according to a particular revenue model to generate income.
-
B.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
C.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
D.
hasSecondaryRevenueModel
Indicates that an entity has an additional, non-primary way of generating revenue beyond its main business model.
-
E.
revenueCollectionRelationship
chosen
Indicates a relationship where one entity is responsible for collecting or receiving revenue on behalf of or from another entity.
- F. None of above.
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_69f76e3154908190a6f702671c2bea08 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:08 p.m.