Triple
T25425237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RDSEED |
E637100
|
entity |
| Predicate | outputQuality |
P158288
|
FINISHED |
| Object | cryptographically secure random seeds |
—
|
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: cryptographically secure random seeds | Statement: [RDSEED, outputQuality, cryptographically secure random seeds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: outputQuality Context triple: [RDSEED, outputQuality, cryptographically secure random seeds]
-
A.
imageQuality
Indicates the assessed level or degree of visual clarity, detail, and overall fidelity of an image.
-
B.
printingQuality
Indicates the level or standard of how well something is printed, such as clarity, sharpness, and overall print fidelity.
-
C.
storageQuality
Indicates the degree or standard of how well something is stored, such as its preservation, safety, or suitability for use.
-
D.
videoQuality
Indicates the level or standard of clarity, resolution, and overall visual fidelity associated with a given video.
-
E.
hasPerceptualQuality
Indicates that something possesses a particular sensory or perceptual characteristic, such as a color, sound, texture, taste, or smell.
- F. None of above. chosen
Provenance (4 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6bf25c881909f049d5393927bfb |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 21, 2026, 1:57 p.m.