Triple
T7414739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AES-CCMP |
E171100
|
entity |
| Predicate | MACAlgorithm |
P21840
|
FINISHED |
| Object | CBC-MAC over AES |
—
|
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: CBC-MAC over AES | Statement: [AES-CCMP, MACAlgorithm, CBC-MAC over AES]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MACAlgorithm Context triple: [AES-CCMP, MACAlgorithm, CBC-MAC over AES]
-
A.
usesEncryptionAlgorithm
Indicates that one entity applies or relies on a specific encryption algorithm to protect data or communications.
-
B.
algorithmType
chosen
Indicates the specific kind or category of algorithm associated with an entity or process.
-
C.
blockCipherMode
Indicates the specific operational mode used by a block cipher to process data (e.g., how blocks are chained, padded, or transformed during encryption/decryption).
-
D.
cryptographicModel
Indicates a relationship where one entity serves as, or is based on, a particular cryptographic scheme, framework, or formal model.
-
E.
Merkle–Damgård strengthening
Indicates that a hash function construction applies Merkle–Damgård strengthening, meaning the message is padded with its length (and possibly other structured padding) before processing to help ensure collision resistance and proper security properties.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:11 p.m.