Triple
T17676443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SparseMatrixCSC |
E440652
|
entity |
| Predicate | memoryEfficiencyReason |
P128517
|
FINISHED |
| Object | stores only nonzero entries |
—
|
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: stores only nonzero entries | Statement: [SparseMatrixCSC, memoryEfficiencyReason, stores only nonzero entries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memoryEfficiencyReason Context triple: [SparseMatrixCSC, memoryEfficiencyReason, stores only nonzero entries]
-
A.
marginEfficiency
Indicates how effectively the margin between revenue and costs is generated or utilized in a given context.
-
B.
sampleEfficiency
Indicates how effectively a method or system learns or performs using a limited number of samples or data points.
-
C.
maximumEfficiency
Indicates that an entity operates at its highest possible level of performance or productivity under given conditions.
-
D.
moreEfficientThan
Indicates that one entity performs a task or uses resources with greater efficiency than another entity.
-
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. 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6d9ab88190ab0e25eac8b0101c |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:01 a.m.