Triple
T32379772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zassenhaus algorithm for factoring polynomials over the rationals |
E827382
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | symbolic computation method |
C410
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: symbolic computation method Context triple: [Zassenhaus algorithm for factoring polynomials over the rationals, instanceOf, symbolic computation method]
-
A.
mathematical method
chosen
A mathematical method is a systematic procedure or algorithm used to solve problems, prove results, or analyze structures within mathematics.
-
B.
pioneer in symbolic computation
A pioneer in symbolic computation is an individual or entity that significantly advances the theory, algorithms, or systems enabling computers to manipulate and reason about mathematical symbols and expressions exactly rather than numerically.
-
C.
method in differential equations
A method in differential equations is a systematic procedure or algorithm used to find exact or approximate solutions to equations involving unknown functions and their derivatives.
-
D.
Gröbner basis algorithm
A Gröbner basis algorithm is a computational procedure that transforms a set of multivariate polynomials into a special generating set (a Gröbner basis) that simplifies solving and analyzing polynomial ideal problems such as solving systems of equations, ideal membership, and elimination.
-
E.
numerical integration method for ordinary differential equations
A numerical integration method for ordinary differential equations is an algorithmic procedure that approximates the solution of an ODE over discrete steps by iteratively updating the dependent variable using information about its derivative.
- F. None of above.
Provenance (1 batch)
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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:51 a.m.