Triple
T272174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diffie–Hellman key exchange |
E5655
|
entity |
| Predicate | threatModel |
P3815
|
FINISHED |
| Object | passive eavesdroppers |
—
|
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: passive eavesdroppers | Statement: [Diffie–Hellman key exchange, threatModel, passive eavesdroppers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatModel Context triple: [Diffie–Hellman key exchange, threatModel, passive eavesdroppers]
-
A.
threat
Indicates a relationship where one entity expresses or poses potential harm, danger, or negative consequences toward another entity.
-
B.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
C.
securityAspect
chosen
Indicates a relationship where something pertains to, represents, or characterizes a particular aspect or dimension of security.
-
D.
majorSecurityIssue
Indicates that the subject faces or causes a significant security vulnerability or threat.
-
E.
securityMechanism
Indicates a relationship where one entity serves as a means or method to protect another entity from threats, vulnerabilities, or unauthorized actions.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.