Triple
T11084464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dynkin formula |
E262081
|
entity |
| Predicate | stateSpace |
P51618
|
FINISHED |
| Object | general measurable state space |
—
|
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: general measurable state space | Statement: [Dynkin formula, stateSpace, general measurable state space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateSpace Context triple: [Dynkin formula, stateSpace, general measurable state space]
-
A.
typicalStateSpace
chosen
Indicates the usual or standard set of states in which an entity, system, or process is considered to operate.
-
B.
stateRepresentation
Indicates that one entity serves as a depiction, model, or encoding of the condition, configuration, or status of another entity.
-
C.
seedSpace
Indicates a relationship where an entity provides or occupies an initial area, context, or capacity from which growth, development, or further allocation can begin.
-
D.
actionSpaceType
Indicates the type or category of action space in which an agent or system can operate (e.g., discrete, continuous, or mixed).
-
E.
observationSpace
Indicates the defined set of possible observations or sensory inputs that an agent can receive from its environment.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799c0cc3081908448cfb26c08daf5 |
completed | April 9, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.