Triple
T27589408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenDaylight |
E699758
|
entity |
| Predicate | supportsYANGModels |
P137919
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [OpenDaylight, supportsYANGModels, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsYANGModels Context triple: [OpenDaylight, supportsYANGModels, true]
-
A.
supportsNETCONF
Indicates that one entity provides or is compatible with NETCONF (Network Configuration Protocol) functionality for another entity.
-
B.
supportedModel
chosen
Indicates that one entity provides compatibility with, or operational backing for, a particular model.
-
C.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
D.
supportsModelFamily
Indicates that one entity provides compatibility, functionality, or resources necessary for the operation or use of a particular model family.
-
E.
supportsModelingOf
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_69ef6a4d71f081909a1235763206b691 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
Created at: April 27, 2026, 2:05 p.m.