Triple
T25425779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel Pentium II |
E637111
|
entity |
| Predicate | L1CacheType |
P158297
|
FINISHED |
| Object | split instruction and data cache |
—
|
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: split instruction and data cache | Statement: [Intel Pentium II, L1CacheType, split instruction and data cache]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: L1CacheType Context triple: [Intel Pentium II, L1CacheType, split instruction and data cache]
-
A.
L1Cache
Indicates a relationship where data or instructions are stored or accessed in the first-level (closest, fastest) cache memory associated with a processor core.
-
B.
l2CacheType
Indicates the specific configuration or design category of an entity’s level-2 (L2) cache in a memory hierarchy.
-
C.
l1CacheSize
Indicates the size or capacity of an entity’s level-1 (L1) cache memory.
-
D.
L2Cache
Indicates that one entity functions as a level-2 cache for another, storing intermediate data or results to speed up repeated access or computation.
-
E.
l1CachePerLittleCore
Indicates the size or capacity of the level-1 cache associated with each little (low-power) core in a processor.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6bfdb748190abfd40ed1838d9aa |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 21, 2026, 1:57 p.m.