Triple
T9740832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sign in with Apple |
E236179
|
entity |
| Predicate | privacyDesign |
P15689
|
FINISHED |
| Object | minimal data collection |
—
|
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: minimal data collection | Statement: [Sign in with Apple, privacyDesign, minimal data collection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: privacyDesign Context triple: [Sign in with Apple, privacyDesign, minimal data collection]
-
A.
privacyProperty
Indicates that one entity has a characteristic, rule, or condition specifically related to privacy in the context of the relationship.
-
B.
privacyCharacteristic
chosen
Indicates the specific privacy-related property or feature that characterizes how information is handled, protected, or exposed in a given context.
-
C.
protectedDesignation
Indicates that one entity has an officially recognized and legally protected designation or status in relation to another entity.
-
D.
dataPolicy
Indicates that one entity defines or governs how data related to another entity is collected, used, stored, or shared.
-
E.
security
Indicates that an entity provides protection, safety measures, or safeguards to another entity or against specific threats or risks.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2af3e48190b83a442cd0e84062 |
completed | April 1, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:22 p.m.