Triple
T4051090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD64 architecture |
E84586
|
entity |
| Predicate | generalPurposeRegistersCount |
P17355
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [AMD64 architecture, generalPurposeRegistersCount, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generalPurposeRegistersCount Context triple: [AMD64 architecture, generalPurposeRegistersCount, 16]
-
A.
generalPurposeRegisters
Indicates that the relationship involves general-purpose registers used to hold data or addresses during computation or instruction execution.
-
B.
numberOfGeneralPurposeRegisters
chosen
Indicates the quantity of general-purpose registers associated with or available in a given computing context.
-
C.
segmentRegisterCount
Indicates the number of register units associated with or allocated to a particular segment in a system or structure.
-
D.
instructionSetSize
Indicates the size or number of instructions defined in an instruction set.
-
E.
coreCountCPU
Indicates the number of processing cores that a CPU has.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb8539148190990468c1429be9dd |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.