Triple
T1937735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augmented Transition Network |
E41481
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | finite state machine formalism |
C7185
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: finite state machine formalism Context triple: [Augmented Transition Network, instanceOf, finite state machine formalism]
-
A.
formal language classification scheme
A formal language classification scheme is a systematic framework for categorizing formal languages based on their generative or recognitional power, typically using hierarchies such as the Chomsky hierarchy.
-
B.
hierarchy of formal grammars
A hierarchy of formal grammars is an organized classification of grammars into levels based on their generative power and structural constraints, such as the Chomsky hierarchy from regular to recursively enumerable languages.
-
C.
model of computation
chosen
A model of computation is an abstract mathematical framework that defines how algorithms are represented and executed, specifying the rules, operations, and resources available for performing computations.
-
D.
framework in generative grammar
A framework in generative grammar is a theoretical system of principles and formal mechanisms used to model and explain the innate structure and rules underlying human language.
-
E.
cellular automaton
A cellular automaton is a discrete computational model consisting of a grid of cells, each in one of a finite number of states, that evolve over time according to simple local rules based on the states of neighboring cells.
- F. None of above.
Provenance (1 batch)
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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
Created at: March 4, 2026, 7:36 p.m.