Triple
T36933748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Pro (11-inch, 1st generation) |
E913554
|
entity |
| Predicate | higherRAMAppliesTo |
P194967
|
FINISHED |
| Object | 1 TB storage model |
—
|
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: 1 TB storage model | Statement: [iPad Pro (11-inch, 1st generation), higherRAMAppliesTo, 1 TB storage model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherRAMAppliesTo Context triple: [iPad Pro (11-inch, 1st generation), higherRAMAppliesTo, 1 TB storage model]
-
A.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
-
B.
typicalRAMRange
Indicates the usual or commonly expected range of RAM capacity associated with an entity.
-
C.
expandableRAM
Indicates that a device’s RAM can be increased beyond its original capacity, typically by adding or upgrading memory modules.
-
D.
typicalRAMRangeMB
Indicates the usual or expected range of RAM capacity, measured in megabytes, associated with an entity.
-
E.
videoRAMUpgradeable
Indicates that the amount of video RAM in a device can be increased or replaced beyond its original configuration.
- 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_69f76e896c988190880c130e01303dd4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd91a5dad8819093eeeef527027890 |
completed | May 8, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69fd8f65fe9081908902500a3228d935 |
completed | May 8, 2026, 7:23 a.m. |
| PDg | Predicate description generation | batch_69fd91a44268819081b372296e3aa116 |
completed | May 8, 2026, 7:32 a.m. |
Created at: May 3, 2026, 4:13 p.m.