Triple
T9675016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA Triton Inference Server |
E234124
|
entity |
| Predicate | supportsMultiModelServing |
P89566
|
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: [NVIDIA Triton Inference Server, supportsMultiModelServing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMultiModelServing Context triple: [NVIDIA Triton Inference Server, supportsMultiModelServing, true]
-
A.
supportsModelVariant
Indicates that one entity is capable of operating with, being compatible with, or otherwise accommodating a specific variant of a model.
-
B.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
C.
supportsModelFamily
Indicates that one entity provides compatibility, functionality, or resources necessary for the operation or use of a particular model family.
-
D.
hasLanguageModel
Indicates that an entity possesses, uses, or is associated with a particular language model.
-
E.
supportsInferenceOf
Indicates that one entity provides a logical basis or justification for concluding or deriving another 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c6d6dd48190a77c486337a58cb6 |
completed | April 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b5d40c8190850ad7a351445f32 |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd9408c848190b84dd74d87f76273 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:15 p.m.