Triple
T31498399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Pro 15-inch (2018) |
E803609
|
entity |
| Predicate | memoryMax |
P53401
|
FINISHED |
| Object | 32 GB |
—
|
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 GB | Statement: [MacBook Pro 15-inch (2018), memoryMax, 32 GB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memoryMax Context triple: [MacBook Pro 15-inch (2018), memoryMax, 32 GB]
-
A.
mainMemorySize
Indicates the relationship specifying the size or capacity of an entity's main memory.
-
B.
flashMemoryMax
Indicates the maximum flash memory capacity associated with an entity or component.
-
C.
maxRAMUnofficial
Indicates the maximum amount of RAM that can be used or installed in an unofficial or unsupported configuration.
-
D.
maxRAMOfficial
chosen
Indicates the officially specified maximum amount of RAM that is supported or allowed for an entity (such as a device or system).
-
E.
maximumUsage
Indicates the highest allowable or observed amount, frequency, or extent to which something can be used within a defined context or period.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 30, 2026, 9:42 p.m.