Triple
T25425449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLMUL |
E637104
|
entity |
| Predicate | bitwiseInterpretation |
P158294
|
FINISHED |
| Object | treats operands as polynomials over GF(2) |
—
|
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: treats operands as polynomials over GF(2) | Statement: [CLMUL, bitwiseInterpretation, treats operands as polynomials over GF(2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitwiseInterpretation Context triple: [CLMUL, bitwiseInterpretation, treats operands as polynomials over GF(2)]
-
A.
bitRepresentation
Indicates that one entity is the binary (bit-level) representation or encoding of another entity.
-
B.
appliedBitwise
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.
-
C.
bitOrder
Indicates the ordering or sequence of bits within a binary representation, such as which bit positions are considered first or most significant.
-
D.
bitSlice
Indicates taking a contiguous subset of bits from a larger bit sequence, defined by specified start and end positions.
-
E.
bitWidth
Indicates the number of bits used to represent or encode a given value, type, or data element.
- 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_69f5f6bfdb748190abfd40ed1838d9aa |
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.