Triple
T29328427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Polly |
E743716
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cloud-based text-to-speech service |
C9068
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: cloud-based text-to-speech service Context triple: [Amazon Polly, instanceOf, cloud-based text-to-speech service]
-
A.
text-to-speech model
chosen
A text-to-speech model is a system that converts written text into natural-sounding spoken audio using linguistic analysis and speech synthesis techniques.
-
B.
speech recognition API
A speech recognition API is a software interface that converts spoken language into machine-readable text or commands, enabling applications to process and respond to voice input.
-
C.
voice application platform feature
A voice application platform feature is a functional capability within a voice-enabled system that allows developers or users to create, manage, and enhance interactive voice experiences through tools like speech recognition, natural language understanding, and integration with external services.
-
D.
voice service continuity mechanism
A voice service continuity mechanism is a system that ensures ongoing, uninterrupted voice communication by seamlessly maintaining or transferring active calls across different networks, technologies, or coverage areas.
-
E.
speech foundation model
A speech foundation model is a large-scale, pre-trained neural network designed to understand, generate, and transform spoken language across diverse tasks, languages, and acoustic conditions.
- F. None of above.
Provenance (1 batch)
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_69f09125f784819080f4e9fce9fe624f |
completed | April 28, 2026, 10:51 a.m. |
Created at: April 28, 2026, 1:28 p.m.