Triple
T18896758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoare partition scheme |
E462227
|
entity |
| Predicate | advantageOverLomuto |
P83524
|
FINISHED |
| Object | fewer swaps on average |
—
|
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: fewer swaps on average | Statement: [Hoare partition scheme, advantageOverLomuto, fewer swaps on average]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOverLomuto Context triple: [Hoare partition scheme, advantageOverLomuto, fewer swaps on average]
-
A.
worstCasePerformanceComparedToQuicksort
Indicates that the worst-case performance of one algorithm is being compared to that of the Quicksort algorithm.
-
B.
isMoreEfficientThan
Indicates that one entity performs a task or uses resources in a way that achieves the same or better outcome with less time, effort, or cost than another entity.
-
C.
moreEfficientThan
chosen
Indicates that one entity performs a task or uses resources with greater efficiency than another entity.
-
D.
averageCasePerformanceComparedToQuicksort
Indicates how the algorithm’s average-case performance compares to that of Quicksort.
-
E.
advantageOverDeterministicMethods
Indicates that one method or approach provides a benefit or superior performance compared to deterministic methods.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c47f6c948190918ade08bb88f1fd |
completed | April 20, 2026, 6:15 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.