Triple
T33027036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BLAKE2s |
E845069
|
entity |
| Predicate | preimageResistanceBits |
P91185
|
FINISHED |
| Object | 256 bits |
—
|
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: 256 bits | Statement: [BLAKE2s, preimageResistanceBits, 256 bits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preimageResistanceBits Context triple: [BLAKE2s, preimageResistanceBits, 256 bits]
-
A.
preimageResistance
chosen
Indicates that it is computationally infeasible to find any input that maps to a given output under the function (e.g., a cryptographic hash), even when that output is known.
-
B.
secondPreimageResistance
Indicates that, given one input and its output under a function (typically a hash), it is computationally infeasible to find a different input that produces the same output.
-
C.
collisionResistanceTarget
Indicates that the entity serves as the designated object or system that a collision-resistance mechanism is intended to protect against successful collisions.
-
D.
Merkle–Damgård strengthening
Indicates that a hash function construction applies Merkle–Damgård strengthening, meaning the message is padded with its length (and possibly other structured padding) before processing to help ensure collision resistance and proper security properties.
-
E.
digestSize
Indicates the size or length of a computed digest (such as a hash or checksum) produced from some data.
- 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:23 a.m.