Triple
T25550446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVX-512 |
E640424
|
entity |
| Predicate | opmaskRegisterCount |
P158640
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [AVX-512, opmaskRegisterCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opmaskRegisterCount Context triple: [AVX-512, opmaskRegisterCount, 8]
-
A.
numberOfGeneralPurposeRegisters
Indicates the quantity of general-purpose registers associated with or available in a given computing context.
-
B.
segmentRegisterCount
Indicates the number of register units associated with or allocated to a particular segment in a system or structure.
-
C.
numberOfRegisters
Indicates the total count of registers associated with or contained in a given entity.
-
D.
floatingPointRegisterCount
Indicates the number of floating-point registers associated with an entity (such as a processor or execution context).
-
E.
numberOfIndexRegisters
Indicates the quantity of index registers associated with or available to a given entity (such as a processor or instruction set).
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8c583e48190a2a1f65d80a2b589 |
completed | May 2, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69f468421ba08190880eac99135e5970 |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f46d361c348190b5fdfd805ecde01b |
completed | May 1, 2026, 9:07 a.m. |
Created at: April 21, 2026, 3:36 p.m.