Triple
T32807752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CSR (Compressed Sparse Row) |
E839061
|
entity |
| Predicate | advantageOverDense |
P83524
|
FINISHED |
| Object | reduces memory for highly sparse matrices |
—
|
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: reduces memory for highly sparse matrices | Statement: [CSR (Compressed Sparse Row), advantageOverDense, reduces memory for highly sparse matrices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOverDense Context triple: [CSR (Compressed Sparse Row), advantageOverDense, reduces memory for highly sparse matrices]
-
A.
moreEfficientThan
chosen
Indicates that one entity performs a task or uses resources with greater efficiency than another entity.
-
B.
advantageOverDeterministicMethods
Indicates that one method or approach provides a benefit or superior performance compared to deterministic methods.
-
C.
moreAdaptiveThan
Indicates that one entity is better able to adjust or respond effectively to changes or varying conditions than another entity.
-
D.
advantageOverCellBasedASICs
Indicates that one entity possesses a benefit or superiority when compared to cell-based ASICs in a given context.
-
E.
advantageOverAutoregressiveModels
Indicates that one method, system, or approach possesses benefits or superior performance compared to autoregressive models.
- 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_69f3493d35208190b4351b4e85f2fa16 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:15 a.m.