Triple
T15860733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTL* |
E384578
|
entity |
| Predicate | modelCheckingComplexity |
P28756
|
FINISHED |
| Object | PSPACE-complete for state formulas |
—
|
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: PSPACE-complete for state formulas | Statement: [CTL*, modelCheckingComplexity, PSPACE-complete for state formulas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelCheckingComplexity Context triple: [CTL*, modelCheckingComplexity, PSPACE-complete for state formulas]
-
A.
hasReasoningComplexity
Indicates that an action, process, or decision involves a certain level or type of cognitive or logical complexity in its reasoning.
-
B.
hasComplexity
chosen
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
C.
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.
-
D.
controlsComplexityBy
Indicates that one entity manages, limits, or regulates the complexity of another entity, process, or system.
-
E.
parsingComplexity
Indicates the level of difficulty or computational effort required to parse or analyze a given input 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:50 a.m.