Triple
T8284607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | o32 ABI |
E193758
|
entity |
| Predicate | floatingPointRegisterSize |
P4121
|
FINISHED |
| Object | 32 bits |
—
|
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: 32 bits | Statement: [o32 ABI, floatingPointRegisterSize, 32 bits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floatingPointRegisterSize Context triple: [o32 ABI, floatingPointRegisterSize, 32 bits]
-
A.
numberOfFloats
Indicates the quantity of floating-point values associated with or contained in an entity.
-
B.
floatType
Indicates that an entity has a specific floating-point data type or is categorized as a floating-point numeric value.
-
C.
numberOfGeneralPurposeRegisters
Indicates the quantity of general-purpose registers associated with or available in a given computing context.
-
D.
bitWidth
chosen
Indicates the number of bits used to represent or encode a given value, type, or data element.
-
E.
segmentRegisterCount
Indicates the number of register units associated with or allocated to a particular segment in a system or structure.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7ad0535081908bb234cfc0e32b32 |
completed | March 31, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:52 p.m.