Triple
T12324383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS Snowball |
E293790
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | AWS Snowball Edge Compute Optimized with GPU |
E293790
|
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: AWS Snowball Edge Compute Optimized with GPU | Statement: [AWS Snowball, hasVariant, AWS Snowball Edge Compute Optimized with GPU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AWS Snowball Edge Compute Optimized with GPU Context triple: [AWS Snowball, hasVariant, AWS Snowball Edge Compute Optimized with GPU]
-
A.
AWS Snowball
chosen
AWS Snowball is a petabyte-scale data transport and edge computing device from Amazon Web Services designed to securely move large amounts of data into and out of the AWS cloud.
-
B.
AWS Snowmobile
AWS Snowmobile is a massive data transfer service that uses secure, truck-sized storage containers to physically move extremely large volumes of data into the AWS cloud.
-
C.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
-
D.
Google TPU
Google TPU is a custom-designed application-specific integrated circuit (ASIC) developed by Google to accelerate machine learning workloads, particularly deep learning inference and training in its data centers.
-
E.
NVIDIA inference platform
The NVIDIA inference platform is a comprehensive suite of hardware and software tools designed to accelerate and optimize AI model deployment and real-time inference across data center, edge, and embedded environments.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4e7e588190b37e2413bc649198 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6346a3f34819091882004ab558347 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:53 p.m.