Triple
T30315620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Root CA |
E771047
|
entity |
| Predicate | trustAnchorFor |
P148457
|
FINISHED |
| Object | Apple PKI hierarchy |
—
|
NE NERFINISHED |
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: Apple PKI hierarchy | Statement: [Apple Root CA, trustAnchorFor, Apple PKI hierarchy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trustAnchorFor Context triple: [Apple Root CA, trustAnchorFor, Apple PKI hierarchy]
-
A.
trustAnchoredVia
Indicates that a relationship of trust is established or justified through a specific intermediary or anchoring mechanism (such as a trusted authority, key, or certificate).
-
B.
trustStoreInclusion
chosen
Indicates that one entity is included as a trusted certificate or key within another entity’s trust store.
-
C.
trustModel
Indicates that one entity relies on or has confidence in the reliability, integrity, or performance of another entity or system.
-
D.
trustPurpose
Indicates that one entity has a specific intended use, goal, or objective for which a trust or trusted arrangement is established with another entity.
-
E.
trustManager
Indicates that one entity relies on and has confidence in another entity to manage or oversee something responsibly.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68193b2b08190a00f08dbba490563 |
completed | May 2, 2026, 10:58 p.m. |
| PD | Predicate disambiguation | batch_69f67603526c81908295a1ece8727c66 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:51 p.m.