Triple
T425479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple M2 |
E8197
|
entity |
| Predicate | memoryBandwidth |
P13752
|
FINISHED |
| Object | 100 GB/s |
—
|
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: 100 GB/s | Statement: [Apple M2, memoryBandwidth, 100 GB/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memoryBandwidth Context triple: [Apple M2, memoryBandwidth, 100 GB/s]
-
A.
memoryType
Indicates the specific category or kind of memory associated with an entity or process.
-
B.
maxUnifiedMemory
Indicates the maximum amount of unified (shared CPU/GPU) memory that can be allocated or used in a given context.
-
C.
bitWidth
Indicates the number of bits used to represent or encode a given value, type, or data element.
-
D.
memoryModel
Indicates a relationship where an entity serves as or uses a specific model or framework for representing, organizing, or managing memory.
-
E.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed56ab481909eec289075496260 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd6736c81909a6ca549f77b4345 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.