Triple
T7088774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Alexa Skills |
E165140
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Alexa capability extension |
C10734
|
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: Alexa capability extension Context triple: [Amazon Alexa Skills, instanceOf, Alexa capability extension]
-
A.
extension language platform
chosen
An extension language platform is a system that embeds or hosts a scripting or domain-specific language to allow users to customize, automate, and extend the functionality of an application or environment.
-
B.
intelligent personal assistant
An intelligent personal assistant is a software agent that uses artificial intelligence to understand user requests, manage tasks, and provide personalized information or services through natural language interaction.
-
C.
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.
-
D.
cross‑device integration framework
A cross-device integration framework is a software architecture that enables seamless communication, data sharing, and coordinated functionality across multiple heterogeneous devices and platforms.
-
E.
omnichannel customer service platform
An omnichannel customer service platform is a unified system that enables businesses to manage and respond to customer interactions seamlessly across multiple channels (such as email, chat, social media, phone, and SMS) from a single interface.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
Created at: March 27, 2026, 2:41 p.m.