Triple
T4416389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knuth–Morris–Pratt algorithm |
E94984
|
entity |
| Predicate | timeComplexityWorstCase |
P27167
|
FINISHED |
| Object | O(n + m) |
—
|
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 + m) | Statement: [Knuth–Morris–Pratt algorithm, timeComplexityWorstCase, O(n + m)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeComplexityWorstCase Context triple: [Knuth–Morris–Pratt algorithm, timeComplexityWorstCase, O(n + m)]
-
A.
timeComplexity
chosen
Indicates the computational growth rate of an algorithm’s resource usage (typically time) as a function of input size.
-
B.
timingMethod
Indicates the method or technique used to measure or record the timing of an event or process.
-
C.
parsingComplexity
Indicates the level of difficulty or computational effort required to parse or analyze a given input or structure.
-
D.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
E.
maximumDepth
Indicates the greatest extent or deepest level reached by something within a given context or structure.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551afb448190a2ce2000193808ac |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:29 p.m.