Triple
T8552032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyper Neo Geo 64 |
E202465
|
entity |
| Predicate | hardwareBitWidth |
P4121
|
FINISHED |
| Object | 64-bit |
—
|
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: 64-bit | Statement: [Hyper Neo Geo 64, hardwareBitWidth, 64-bit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hardwareBitWidth Context triple: [Hyper Neo Geo 64, hardwareBitWidth, 64-bit]
-
A.
bitWidth
chosen
Indicates the number of bits used to represent or encode a given value, type, or data element.
-
B.
busWidthComparedToISA
Indicates how the width of a bus compares to the width defined by a given instruction set architecture (ISA), such as being wider, narrower, or equal.
-
C.
numberOfGeneralPurposeRegisters
Indicates the quantity of general-purpose registers associated with or available in a given computing context.
-
D.
dataPinCount
Indicates the number of data pins associated with or used by an entity in a given context.
-
E.
minimumHeatPerBit
Indicates the least amount of heat that must be generated or dissipated for each unit of information (bit) processed or transmitted in a given context.
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe886fb788190a73e7c76c4f86409 |
completed | March 31, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:19 p.m.