Triple
T26992558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clique problem |
E679893
|
entity |
| Predicate | parameterizedComplexity |
P162024
|
FINISHED |
| Object | W[1]-complete |
—
|
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: W[1]-complete | Statement: [Clique problem, parameterizedComplexity, W[1]-complete]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parameterizedComplexity Context triple: [Clique problem, parameterizedComplexity, W[1]-complete]
-
A.
timeComplexity
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.
hasComplexity
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
D.
parsingComplexity
Indicates the level of difficulty or computational effort required to parse or analyze a given input or structure.
-
E.
assumesComplexityMeasure
Indicates that one entity adopts or takes for granted a particular method or standard for measuring complexity in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621c7d3e0819095b1f327637ae4f9 |
completed | May 2, 2026, 4:09 p.m. |
Created at: April 27, 2026, 6:52 a.m.