Triple
T14984161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cooley–Tukey Fast Fourier Transform algorithm |
E373658
|
entity |
| Predicate | typicalDFTComplexity |
P27167
|
FINISHED |
| Object | O(N^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: O(N^2) | Statement: [Cooley–Tukey Fast Fourier Transform algorithm, typicalDFTComplexity, O(N^2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDFTComplexity Context triple: [Cooley–Tukey Fast Fourier Transform algorithm, typicalDFTComplexity, O(N^2)]
-
A.
timeComplexity
chosen
Indicates the computational growth rate of an algorithm’s resource usage (typically time) as a function of input size.
-
B.
inverseFourierTransform
Indicates the mathematical operation that converts a frequency-domain representation of a signal or function back into its corresponding time- or spatial-domain form.
-
C.
computationalCost
Indicates the amount of computing resources (such as time, memory, or processing power) required to perform a given operation or process.
-
D.
typicalComplexity
Indicates the usual or characteristic level of complexity associated with an entity, process, or situation.
-
E.
isTotallyComplex
Indicates that something possesses a level of complexity that is complete, multifaceted, and not reducible to simpler or purely real/straightforward components.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6ff4a7c8190ab7554f3a1a09b67 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.