Triple
T36151576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVL tree |
E1045598
|
entity |
| Predicate | deleteTimeComplexityWorst |
P27167
|
FINISHED |
| Object | O(log n) |
—
|
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(log n) | Statement: [AVL tree, deleteTimeComplexityWorst, O(log n)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deleteTimeComplexityWorst Context triple: [AVL tree, deleteTimeComplexityWorst, O(log n)]
-
A.
timeComplexity
chosen
Indicates the computational growth rate of an algorithm’s resource usage (typically time) as a function of input size.
-
B.
numberOfSwapsWorstCase
Indicates the maximum number of swap operations required in the worst-case scenario for a given process or algorithm.
-
C.
spaceComplexity
Indicates the relationship between an algorithm and the amount of memory it requires as a function of input size.
-
D.
worstCasePerformanceComparedToQuicksort
Indicates that the worst-case performance of one algorithm is being compared to that of the Quicksort algorithm.
-
E.
numberOfShiftsWorstCase
Indicates the maximum possible number of shifts or repositioning operations required in the most unfavorable or worst-case scenario.
- 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_69f76e37ace88190a906b107d388f5d1 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:08 p.m.