Triple
T25616939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD K6-2 |
E642183
|
entity |
| Predicate | supportsFloatingPointUnit |
P91925
|
FINISHED |
| Object | integrated FPU |
—
|
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: integrated FPU | Statement: [AMD K6-2, supportsFloatingPointUnit, integrated FPU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFloatingPointUnit Context triple: [AMD K6-2, supportsFloatingPointUnit, integrated FPU]
-
A.
hasVectorFloatingPointUnit
Indicates that an entity (typically a processor or core) includes a hardware unit capable of performing floating-point operations on vector (SIMD) data.
-
B.
supportsFloatingPoint
chosen
Indicates that an entity is capable of handling or operating with floating-point (non-integer) numeric values.
-
C.
numberOfFloatingPointUnits
Indicates the quantity of floating-point processing units associated with or contained in an entity.
-
D.
FPU
Indicates that one entity functions as or contains a floating-point unit responsible for performing arithmetic operations on non-integer (floating-point) numbers for another entity or within a system.
-
E.
floatingPointUnitSharing
Indicates that two or more processing units share access to a common floating-point execution resource rather than each having a dedicated one.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: April 21, 2026, 5 p.m.