Triple
T5892207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P versus NP problem |
E131016
|
entity |
| Predicate | involvesComplexityClass |
P62369
|
FINISHED |
| Object | P |
—
|
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: P | Statement: [P versus NP problem, involvesComplexityClass, P]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesComplexityClass Context triple: [P versus NP problem, involvesComplexityClass, P]
-
A.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
B.
complexityClassRelation
chosen
Indicates a relationship between two computational complexity classes, such as inclusion, equivalence, or separation, within the hierarchy of complexity theory.
-
C.
hasReasoningComplexity
Indicates that an action, process, or decision involves a certain level or type of cognitive or logical complexity in its reasoning.
-
D.
timeComplexity
Indicates the computational growth rate of an algorithm’s resource usage (typically time) as a function of input size.
-
E.
computationalClass
Indicates that two entities share the same computational complexity class or that one entity is categorized within a specified computational complexity class.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0334dc8248190b7394dcece362d52 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:58 p.m.