Triple
T11819378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagoner County |
E281083
|
entity |
| Predicate | containsPartOf |
P1393
|
FINISHED |
| Object | Bixby |
E739317
|
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 | Statement: [Wagoner County, containsPartOf, Bixby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bixby Context triple: [Wagoner County, containsPartOf, Bixby]
-
A.
Bixby
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.
Bixby
chosen
Bixby is a suburban city in northeastern Oklahoma, known for its rapid growth and agricultural roots within the Tulsa metropolitan area.
-
C.
Bixby Vision
Bixby Vision is Samsung’s image-recognition and augmented reality feature that lets users identify objects, translate text, and obtain contextual information through their device’s camera.
-
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
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.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5e87e488190905bc3bb6d721e56 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131cbf9708190ba8394fb3508b975 |
completed | April 28, 2026, 10:16 p.m. |
Created at: April 8, 2026, 9:42 p.m.