Triple
T25436596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SSE4.1 |
E637388
|
entity |
| Predicate | supportsFloatingPointOperations |
P120705
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [SSE4.1, supportsFloatingPointOperations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFloatingPointOperations Context triple: [SSE4.1, supportsFloatingPointOperations, true]
-
A.
supportsFloatingPoint
Indicates that an entity is capable of handling or operating with floating-point (non-integer) numeric values.
-
B.
supportsArbitraryPrecisionArithmetic
Indicates that the subject system or component can perform arithmetic operations with numbers of virtually unlimited size and precision, beyond fixed hardware-imposed limits.
-
C.
hasVectorFloatingPointUnit
chosen
Indicates that an entity (typically a processor or core) includes a hardware unit capable of performing floating-point operations on vector (SIMD) data.
-
D.
floatingPointPerformance
Indicates the level of computational capability or efficiency an entity has when performing floating-point arithmetic operations.
-
E.
supportsIntegerOperations
Indicates that the subject is capable of performing or handling operations involving integer values.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 21, 2026, 1:59 p.m.