Triple
T28338309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NIST SP 800-108 |
E717740
|
entity |
| Predicate | PRFExamples |
P41975
|
FINISHED |
| Object | HMAC-based pseudorandom function |
—
|
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: HMAC-based pseudorandom function | Statement: [NIST SP 800-108, PRFExamples, HMAC-based pseudorandom function]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: PRFExamples Context triple: [NIST SP 800-108, PRFExamples, HMAC-based pseudorandom function]
-
A.
baseExamples
Indicates that something serves as a fundamental or illustrative example for understanding or demonstrating another concept, item, or case.
-
B.
extraExample
Indicates that something is provided as an additional, illustrative instance beyond the main or required examples.
-
C.
usedAsExampleIn
chosen
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
D.
centralExample
Indicates that one entity serves as the primary or most representative example of another entity or concept.
-
E.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
- 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64bd68ac08190b35887261657a408 |
completed | May 2, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 12:37 a.m.