Triple
T14990708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexa PenaVega |
E373826
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alexa |
E373824
|
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 | Statement: [Alexa PenaVega, givenName, Alexa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexa Context triple: [Alexa PenaVega, givenName, Alexa]
-
A.
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.
-
B.
Alexa
chosen
Alexa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Alexandra.
-
C.
Alexa Voice Service
Alexa Voice Service is Amazon’s cloud-based voice recognition and natural language processing platform that powers Alexa-enabled devices and allows developers to integrate voice control into their products.
-
D.
Siri
Siri is Apple's intelligent voice-controlled virtual assistant that performs tasks, answers questions, and controls devices across the Apple ecosystem.
-
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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969683348190bb4688f24227af88 |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:53 a.m.