Triple
T9931892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | brainpool curves |
E192665
|
entity |
| Predicate | securityLevelRange |
P60827
|
FINISHED |
| Object | 128-bit to 256-bit security |
—
|
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: 128-bit to 256-bit security | Statement: [brainpool curves, securityLevelRange, 128-bit to 256-bit security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: securityLevelRange Context triple: [brainpool curves, securityLevelRange, 128-bit to 256-bit security]
-
A.
securityLevelDetail
Indicates the specific classification or degree of security associated with an entity, often including nuanced or descriptive information about its protection level.
-
B.
securityLevelComponents
Indicates that a particular security level is composed of, or associated with, a specific set of component elements or factors.
-
C.
encryptionLevel
Indicates the degree or strength of cryptographic protection applied to data or communications.
-
D.
typicalSecurityLevel
chosen
Indicates the usual or standard security level that is generally applied or expected in a given context or system.
-
E.
securityGranularity
Indicates the level of detail or specificity at which security controls, permissions, or protections are defined and applied within a system or context.
- 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_69ca82dd978c8190947124ab0d3315ac |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5b54f348190b8e70e7beff6098a |
completed | April 2, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:43 p.m.