Triple
T32092475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIPS R2000 |
E819631
|
entity |
| Predicate | supportsHardwareMultiply |
P206177
|
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: [MIPS R2000, supportsHardwareMultiply, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsHardwareMultiply Context triple: [MIPS R2000, supportsHardwareMultiply, yes]
-
A.
supportsHardwareAcceleration
Indicates that one entity enables or provides hardware-based acceleration capabilities for another entity’s operations or processes.
-
B.
supportsGPUType
Indicates that one entity is compatible with, or capable of operating using, a specified type of GPU.
-
C.
supportsMultisampling
Indicates that an entity provides or enables multisampling functionality, typically for improved rendering quality.
-
D.
supportsHardwareCryptography
Indicates that one entity provides or enables hardware-based cryptographic operations or capabilities for another entity.
-
E.
hasHardware
Indicates that one entity possesses, includes, or is equipped with specific hardware components or devices.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:25 a.m.