Triple
T7088957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echo Studio |
E165143
|
entity |
| Predicate | supportsFeature |
P203
|
FINISHED |
| Object | Alexa Drop In |
E168302
|
NE 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: Alexa Drop In | Statement: [Echo Studio, supportsFeature, Alexa Drop In]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexa Drop In Context triple: [Echo Studio, supportsFeature, Alexa Drop In]
-
A.
alexa.com
alexa.com was a popular web analytics and traffic ranking website that provided insights into the popularity and audience metrics of millions of websites worldwide.
-
B.
Alexa mobile app
chosen
The Alexa mobile app is a companion application that lets users set up, manage, and interact with Amazon’s Alexa voice assistant and compatible smart devices from their smartphones.
-
C.
Alexa
Alexa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Alexandra.
-
D.
Alexa
Alexa is Amazon’s cloud-based virtual assistant that uses voice interaction to control smart devices, answer questions, and perform a variety of digital tasks.
-
E.
Nina virtual assistant
Nina virtual assistant is Nuance Communications’ AI-powered virtual assistant platform designed to automate and enhance customer service interactions across digital and voice channels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e52ec0348190ac090c2fee3edfb8 |
completed | March 27, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c794888abc8190ada2ae826449745a |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:41 p.m.