Triple
T27750418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microsoft Windows games |
E702098
|
entity |
| Predicate | typicalMonetizationModel |
P94216
|
FINISHED |
| Object | premium purchase |
—
|
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: premium purchase | Statement: [Microsoft Windows games, typicalMonetizationModel, premium purchase]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMonetizationModel Context triple: [Microsoft Windows games, typicalMonetizationModel, premium purchase]
-
A.
hasMonetizationFocus
Indicates that one entity is oriented toward or primarily concerned with generating revenue or financial returns from another entity or activity.
-
B.
supportsMonetizationProgram
Indicates that an entity enables or is compatible with a specific monetization program, allowing revenue-generating activities to occur.
-
C.
hasMicrotransactions
Indicates that an item, product, or system includes optional small-scale purchases or payments within its overall experience or usage.
-
D.
payPerView
Indicates a relationship where access to specific content or an event is granted only upon a one-time payment for that individual viewing.
-
E.
usesRevenueModel
chosen
Indicates that one entity applies or operates according to a particular revenue model to generate income.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_6a00037bf4148190a58593d30efdd3f8 |
completed | May 10, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_6a0000b7af608190b718fc4111bcdad8 |
completed | May 10, 2026, 3:51 a.m. |
Created at: April 27, 2026, 4:19 p.m.