Triple
T7934703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAST5 |
E184258
|
entity |
| Predicate | bitOperations |
P76813
|
FINISHED |
| Object | uses modular addition |
—
|
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: uses modular addition | Statement: [CAST5, bitOperations, uses modular addition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitOperations Context triple: [CAST5, bitOperations, uses modular addition]
-
A.
appliedBitwise
chosen
Indicates that a bitwise operation has been performed on one value (or set of values) to produce another, using bit-level logical or arithmetic manipulation.
-
B.
bitSlice
Indicates taking a contiguous subset of bits from a larger bit sequence, defined by specified start and end positions.
-
C.
bitRepresentation
Indicates that one entity is the binary (bit-level) representation or encoding of another entity.
-
D.
bitWidth
Indicates the number of bits used to represent or encode a given value, type, or data element.
-
E.
bitLengthFactorization
Indicates a relationship where the bit-length of a number is determined or constrained by the factorization of that number.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aeb132c8190bea4906aaf51b869 |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:08 p.m.