Triple
T7835885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EVPN |
E181689
|
entity |
| Predicate | controlPlaneType |
P79284
|
FINISHED |
| Object | control-plane-based MAC learning |
—
|
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-plane-based MAC learning | Statement: [EVPN, controlPlaneType, control-plane-based MAC learning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlPlaneType Context triple: [EVPN, controlPlaneType, control-plane-based MAC learning]
-
A.
controlPlaneEntity
Indicates that one entity functions as part of, or in association with, a system’s control plane, managing or coordinating control-related operations for that system.
-
B.
typeOfCluster
Indicates that one entity is classified as a specific kind or category of cluster in relation to another entity.
-
C.
deploymentType
Indicates the manner or configuration in which a system, application, or component is deployed or made operational.
-
D.
typeOfDeployment
Indicates the specific manner or configuration in which something (such as a system, application, or resource) is deployed or made operational.
-
E.
acceleratorType
Indicates the kind or category of accelerator associated with or used by an entity.
- F. None of above. chosen
Provenance (4 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064cb7e081909e88419863d94dfe |
completed | March 30, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:46 p.m.