Triple
T3666063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bixby |
E77760
|
entity |
| Predicate | feature |
P374
|
FINISHED |
| Object | Bixby Vision |
E77760
|
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: Bixby Vision | Statement: [Bixby, feature, Bixby Vision]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bixby Vision Context triple: [Bixby, feature, Bixby Vision]
-
A.
Bixby
chosen
Bixby is Samsung's proprietary virtual assistant designed to enable voice control, smart device integration, and contextual assistance across the company's ecosystem of products.
-
B.
Google Lens
Google Lens is an image recognition and search tool by Google that uses artificial intelligence to identify objects, text, and scenes from a device’s camera or photos and provide relevant information or actions.
-
C.
Echo Show
Echo Show is Amazon’s smart display device that combines Alexa voice assistance with a touchscreen for visual interactions like video calls, streaming, and smart home control.
-
D.
Siri
Siri is Apple's intelligent voice-controlled virtual assistant that performs tasks, answers questions, and controls devices across the Apple ecosystem.
-
E.
Landing AI
Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc40188988190b1b7ac9c8240a5ff |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4884bd50c8190a334e9aadc734364 |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.