Triple
T26318514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FlashArray |
E662036
|
entity |
| Predicate | dataProtectionFeature |
P160243
|
FINISHED |
| Object | snapshots |
—
|
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: snapshots | Statement: [FlashArray, dataProtectionFeature, snapshots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataProtectionFeature Context triple: [FlashArray, dataProtectionFeature, snapshots]
-
A.
protectsFeature
Indicates that one entity safeguards, preserves, or defends a particular feature or characteristic of another entity.
-
B.
protectionType
Indicates the kind or method of protection that is applied to or associated with an entity.
-
C.
hasDataProtectionAuthority
Indicates that an entity is subject to, overseen by, or associated with a specific data protection authority responsible for regulating its handling of personal data.
-
D.
protectionPolicy
Indicates that one entity establishes or enforces rules or measures to safeguard another entity from harm, loss, or risk.
-
E.
dataProtectionTradeoff
Indicates a relationship where enhancing data protection or privacy comes at the cost of reduced utility, accessibility, or efficiency in data use, and vice versa.
- 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60f299fd0819089685b371ddfae1b |
completed | May 2, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 26, 2026, 10:26 p.m.