Triple
T5016062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | App Store Small Business Program |
E112742
|
entity |
| Predicate | appliesToRevenueType |
P61523
|
FINISHED |
| Object | net revenue after refunds and taxes |
—
|
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: net revenue after refunds and taxes | Statement: [App Store Small Business Program, appliesToRevenueType, net revenue after refunds and taxes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToRevenueType Context triple: [App Store Small Business Program, appliesToRevenueType, net revenue after refunds and taxes]
-
A.
appliesToProductType
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
-
B.
appliesToServiceType
Indicates that something is relevant or applicable specifically to a particular type or category of service.
-
C.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
D.
hasRateType
Indicates the specific category or scheme under which a rate (such as a price, fee, or interest) is defined or applied.
-
E.
appliesToPropertyType
Indicates that something (such as a rule, constraint, or operation) is relevant to or valid for a specific type of property.
- F. None of above. chosen
Provenance (4 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd732f4c5c8190b90f8e4daab458ee |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714ecfe08190b5830cfc1c74fa17 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:35 p.m.