Triple
T14087167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | QCOW (via conversion) |
E339026
|
entity |
| Predicate | storageOptimization |
P32130
|
FINISHED |
| Object | on-demand allocation |
—
|
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: on-demand allocation | Statement: [QCOW (via conversion), storageOptimization, on-demand allocation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storageOptimization Context triple: [QCOW (via conversion), storageOptimization, on-demand allocation]
-
A.
storageOption
Indicates how or where something is stored, specifying the chosen method, medium, or configuration for its storage.
-
B.
storageOrgan
Indicates that one entity serves as a storage organ (a specialized structure for storing substances like nutrients or water) for another entity.
-
C.
spaceUsage
Indicates how much physical or storage space is occupied or utilized by an entity relative to the total available space.
-
D.
optimize
chosen
Indicates improving a process, system, or outcome to achieve the best possible performance or efficiency under given constraints.
-
E.
powerOptimizationFor
Indicates a relationship where one entity is used to improve, manage, or optimize the power consumption or power efficiency of another entity.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee1ce88819091c983286289337e |
completed | April 14, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.