Triple
T18205283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VisionEncoderDecoderModel |
E435885
|
entity |
| Predicate | supportsBatchInference |
P86209
|
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: [VisionEncoderDecoderModel, supportsBatchInference, True]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBatchInference Context triple: [VisionEncoderDecoderModel, supportsBatchInference, True]
-
A.
supportsMultiModelServing
Indicates that an entity is capable of serving multiple models concurrently within the same system or environment.
-
B.
supportsInferenceOf
Indicates that one entity provides a logical basis or justification for concluding or deriving another entity.
-
C.
supportsBatchProcessing
chosen
Indicates that the subject can handle multiple items or tasks in a single grouped operation rather than processing them individually.
-
D.
supportsPretrainedModels
Indicates that an entity provides compatibility with or functionality for using pretrained models.
-
E.
supportsQuantization
Indicates that one entity is capable of operating with, or is compatible with, quantized representations or computations of 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.