Triple
T11187715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro by T-Mobile |
E264715
|
entity |
| Predicate | usesBillingModel |
P97754
|
FINISHED |
| Object | prepaid billing |
—
|
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: prepaid billing | Statement: [Metro by T-Mobile, usesBillingModel, prepaid billing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBillingModel Context triple: [Metro by T-Mobile, usesBillingModel, prepaid billing]
-
A.
usesRevenueModel
Indicates that one entity applies or operates according to a particular revenue model to generate income.
-
B.
usesBusinessModel
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
C.
usesLicensingModel
Indicates that one entity employs or applies a particular licensing model in its operations or offerings.
-
D.
costModel
Indicates the pricing or cost-structure relationship applied to an entity, defining how its costs are calculated or charged.
-
E.
billingMetric
Indicates a relationship where a specific metric or measure is used as the basis for calculating billing or charges between entities.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ad143481908d5dacc95837ecfd |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.