Triple
T18281225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIV mode |
E437867
|
entity |
| Predicate | supportsRandomNonce |
P34885
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [SIV mode, supportsRandomNonce, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsRandomNonce Context triple: [SIV mode, supportsRandomNonce, false]
-
A.
usesNonce
Indicates that one entity employs a nonce (a unique, typically one-time-use value) as part of its interaction or operation with another entity.
-
B.
requiresNonceUniqueness
Indicates that the action or process demands each nonce value be unique, preventing reuse across operations or transactions.
-
C.
variantNonceSize
Indicates that there is a specific or differing size of nonce associated with a given variant in a cryptographic or protocol context.
-
D.
isDeterministicWithFixedNonceAndKey
chosen
Indicates that the outcome of an operation is fully determined and repeatable when the same nonce and key are used, with no additional randomness involved.
-
E.
requiresKeyAndNonceUniqueness
Indicates that the operation or protocol demands both a unique key and a unique nonce for each use or session to ensure security.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50056ea0481908d66bf263ac80c75 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.