Triple
T4051130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TicPods |
E84587
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | Amazon Alexa |
E31217
|
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: Amazon Alexa | Statement: [TicPods, supports, Amazon Alexa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon Alexa Context triple: [TicPods, supports, Amazon Alexa]
-
A.
Alexa
Alexa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Alexandra.
-
B.
Alexa
chosen
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.
-
C.
Amazon Echo
Amazon Echo is a line of smart speakers developed by Amazon that features the voice-controlled virtual assistant Alexa for tasks like playing music, controlling smart home devices, and answering questions.
-
D.
Amazon Alexa Skills
Amazon Alexa Skills are voice-driven apps that extend Alexa’s capabilities, enabling users to perform a wide range of tasks and access services through spoken commands.
-
E.
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.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb8539148190990468c1429be9dd |
completed | March 9, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55659256081909154569cedd1694a |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.