Triple
T27584442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OMT method |
E699655
|
entity |
| Predicate | dynamicModelRepresents |
P113729
|
FINISHED |
| Object | control aspects of the 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: control aspects of the system | Statement: [OMT method, dynamicModelRepresents, control aspects of the system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dynamicModelRepresents Context triple: [OMT method, dynamicModelRepresents, control aspects of the system]
-
A.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
B.
entityRepresents
Indicates that one entity stands for, symbolizes, or serves as a representation of another entity.
-
C.
designModel
Indicates that one entity creates, specifies, or defines the structure or behavior of another entity as a model or blueprint.
-
D.
modeledWith
chosen
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
E.
drawingModel
Indicates that one entity serves as a drawing or visual representation model used to depict, design, or illustrate another entity.
- 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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63018926481908ab0101d087a7714 |
completed | May 2, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:03 p.m.