Triple
T14086573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RISC I |
E339011
|
entity |
| Predicate | numberOfRegisters |
P112754
|
FINISHED |
| Object | 32 |
—
|
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 | Statement: [RISC I, numberOfRegisters, 32]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegisters Context triple: [RISC I, numberOfRegisters, 32]
-
A.
numberOfGeneralPurposeRegisters
Indicates the quantity of general-purpose registers associated with or available in a given computing context.
-
B.
numberOfIndexRegisters
Indicates the quantity of index registers associated with or available to a given entity (such as a processor or instruction set).
-
C.
segmentRegisterCount
Indicates the number of register units associated with or allocated to a particular segment in a system or structure.
-
D.
generalPurposeRegisters
Indicates that the relationship involves general-purpose registers used to hold data or addresses during computation or instruction execution.
-
E.
floatingPointRegisterCount
Indicates the number of floating-point registers associated with an entity (such as a processor or execution context).
- 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_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. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:21 p.m.