Triple
T17499751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS Auto Scaling |
E426158
|
entity |
| Predicate | supportsScalingType |
P24486
|
FINISHED |
| Object | dynamic scaling |
—
|
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: dynamic scaling | Statement: [AWS Auto Scaling, supportsScalingType, dynamic scaling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsScalingType Context triple: [AWS Auto Scaling, supportsScalingType, dynamic scaling]
-
A.
requiresFeatureScaling
Indicates that applying feature scaling is a necessary preprocessing step for the associated data or model.
-
B.
autoscalingType
Indicates the method or strategy by which a system automatically adjusts its resource capacity (such as scaling up or down) in response to changing demand or conditions.
-
C.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
D.
hasInfrastructureScale
Indicates the relative size, capacity, or extent of infrastructure associated with or supporting an entity.
-
E.
supportsSubdirectoryScalability
Indicates that one entity enables or enhances another entity’s ability to efficiently handle growth in the number or depth of its subdirectories.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452112ff0819089c2951baba90102 |
completed | April 19, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f5fbcc8190a6ea9639bf5650da |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:48 a.m.