Triple
T36199047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prim's minimum spanning tree algorithm |
E1047207
|
entity |
| Predicate | timeComplexityWithAdjacencyMatrix |
P27167
|
FINISHED |
| Object | O(V^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(V^2) | Statement: [Prim's minimum spanning tree algorithm, timeComplexityWithAdjacencyMatrix, O(V^2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeComplexityWithAdjacencyMatrix Context triple: [Prim's minimum spanning tree algorithm, timeComplexityWithAdjacencyMatrix, O(V^2)]
-
A.
timeComplexity
chosen
Indicates the computational growth rate of an algorithm’s resource usage (typically time) as a function of input size.
-
B.
spaceComplexity
Indicates the relationship between an algorithm and the amount of memory it requires as a function of input size.
-
C.
parameterizedComplexity
Indicates that the relationship or action is analyzed or characterized in terms of its computational complexity as a function of one or more explicit parameters.
-
D.
numberOfIndependentMatrices
Indicates the count of matrices in a set that are linearly independent from each other.
-
E.
iterationMatrix
Indicates a matrix that represents the transformation or update applied repeatedly in an iterative process or algorithm.
- 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_69f76e414bdc8190996f15a544220a3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:08 p.m.