Triple
T9035282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATA-6 |
E216475
|
entity |
| Predicate | maximumAddressableCapacity |
P3700
|
FINISHED |
| Object | >137 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: >137 GB | Statement: [ATA-6, maximumAddressableCapacity, >137 GB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAddressableCapacity Context triple: [ATA-6, maximumAddressableCapacity, >137 GB]
-
A.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
B.
addressSpaceSize
chosen
Indicates the total amount of addressable memory or identifier range allocated or available within a given address space.
-
C.
maximumVolumeSize
Indicates the largest allowable size or capacity that a volume can have within a given system or context.
-
D.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
E.
maxRAMOfficial
Indicates the officially specified maximum amount of RAM that is supported or allowed for an entity (such as a device or system).
- 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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6abf4af481908d21245332329d99 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.