Triple
T32013560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KL10 |
E817471
|
entity |
| Predicate | supportsExtendedInstructionSet |
P74581
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [KL10, supportsExtendedInstructionSet, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsExtendedInstructionSet Context triple: [KL10, supportsExtendedInstructionSet, yes]
-
A.
hasInstructionSet
Indicates that one entity (typically a processor or system) is defined as using or supporting a particular instruction set.
-
B.
supportsARMv8CryptographyExtensions
Indicates that the subject provides or is compatible with the ARMv8 cryptographic instruction set extensions for hardware-accelerated encryption and related operations.
-
C.
instructionSetExtensions
chosen
Indicates that one entity defines, supports, or includes additional instruction set features or extensions relative to another.
-
D.
supportsNEON
Indicates that one entity provides or enables NEON (ARM Advanced SIMD) instruction set support for another entity.
-
E.
supportsAVX
Indicates that one entity provides or is compatible with AVX (Advanced Vector Extensions) functionality for another entity or operation.
- 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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:15 a.m.