Triple
T14086636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RISC II |
E339012
|
entity |
| Predicate | supportsFloatingPointInCore |
P91925
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [RISC II, supportsFloatingPointInCore, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFloatingPointInCore Context triple: [RISC II, supportsFloatingPointInCore, false]
-
A.
supportsFloatingPoint
chosen
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.
floatingPointPerformance
Indicates the level of computational capability or efficiency an entity has when performing floating-point arithmetic operations.
-
D.
supportsExactRationalArithmetic
Indicates that an entity provides operations on rational numbers using exact arithmetic without rounding or approximation.
-
E.
numberOfFloatingPointUnits
Indicates the quantity of floating-point processing units associated with or contained in an entity.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5edff1b881909ea56dc2429ef2dd |
completed | April 14, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.