Triple
T7415013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galois/Counter Mode |
E171106
|
entity |
| Predicate | vulnerableIf |
P67454
|
FINISHED |
| Object | nonce is reused with same key |
—
|
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: nonce is reused with same key | Statement: [Galois/Counter Mode, vulnerableIf, nonce is reused with same key]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vulnerableIf Context triple: [Galois/Counter Mode, vulnerableIf, nonce is reused with same key]
-
A.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
B.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
C.
associatedWithVulnerability
chosen
Indicates a relationship where an entity is linked to, affected by, or relevant to a specific vulnerability or security weakness.
-
D.
riskIfBreached
Indicates that a breach of the referenced entity or condition would expose or create a potential risk or harm.
-
E.
vulnerabilityType
Indicates the specific kind or category of vulnerability associated with an entity or situation.
- 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_69c6f2c643248190a387abba2f482b25 |
completed | March 27, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.