Triple
T15860743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTL* |
E384578
|
entity |
| Predicate | typicalModelCheckingInput |
P104448
|
FINISHED |
| Object | finite-state transition system |
—
|
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: finite-state transition system | Statement: [CTL*, typicalModelCheckingInput, finite-state transition system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalModelCheckingInput Context triple: [CTL*, typicalModelCheckingInput, finite-state transition system]
-
A.
typicalStateSpace
Indicates the usual or standard set of states in which an entity, system, or process is considered to operate.
-
B.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
C.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
D.
stateModel
Indicates that an entity is represented or governed by a particular state-based model or state machine.
-
E.
supportsModelingOf
chosen
Indicates that one entity provides the capability or functionality needed to represent, simulate, or model another entity or process.
- 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.