Triple
T14874715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charge! |
E349835
|
entity |
| Predicate | hasAdvertisingModel |
P48652
|
FINISHED |
| Object | ad-supported |
—
|
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: ad-supported | Statement: [Charge!, hasAdvertisingModel, ad-supported]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdvertisingModel Context triple: [Charge!, hasAdvertisingModel, ad-supported]
-
A.
hasAdvertisingVisual
Indicates that an entity includes, is associated with, or uses a specific visual element or asset for advertising purposes.
-
B.
usesAdvertisingModel
chosen
Indicates that one entity employs or relies on another entity’s advertising-based business or revenue model.
-
C.
hasAdvertisingSlogan
Indicates that an entity uses or is associated with a particular advertising slogan as part of its promotional or branding activities.
-
D.
hasCellularModel
Indicates that one entity serves as a cellular (cell-based) model or system used to study, represent, or simulate the biological properties or behavior of another entity.
-
E.
hasMarketingElement
Indicates that one entity includes, is associated with, or makes use of a particular marketing-related component or feature.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e3e5d48190a132f2cf012b01e2 |
completed | April 15, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69de8c1a2bcc81908f914e2e2ced65eb |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:55 a.m.