Triple
T4051102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD64 architecture |
E84586
|
entity |
| Predicate | virtualAddressSize |
P3700
|
FINISHED |
| Object | typically 48 bits in early implementations |
—
|
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: typically 48 bits in early implementations | Statement: [AMD64 architecture, virtualAddressSize, typically 48 bits in early implementations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: virtualAddressSize Context triple: [AMD64 architecture, virtualAddressSize, typically 48 bits in early implementations]
-
A.
addressSpaceSize
chosen
Indicates the total amount of addressable memory or identifier range allocated or available within a given address space.
-
B.
numberOfGeneralPurposeRegisters
Indicates the quantity of general-purpose registers associated with or available in a given computing context.
-
C.
stateSizeBytes
Indicates the size of a given state or stateful data in terms of the number of bytes it occupies.
-
D.
videoMemorySize
Indicates the amount of video memory associated with a graphics-related component or device.
-
E.
hasWordSize
Indicates that an entity possesses or is characterized by a specific word length or word-based size.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb8539148190990468c1429be9dd |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef90249e4819095e9e043bc4aa9a6 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.