Triple
T4600412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon S3 |
E100305
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | AWS Snowball |
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 | Statement: [Amazon S3, integratesWith, AWS Snowball]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AWS Snowball Context triple: [Amazon S3, integratesWith, AWS Snowball]
-
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.
AWS Storage Gateway
AWS Storage Gateway is a hybrid cloud storage service that connects on-premises environments to AWS cloud storage for backup, archiving, and disaster recovery.
-
D.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
E.
Amazon S3
Amazon S3 is a scalable, highly durable cloud object storage service from Amazon Web Services used for storing and retrieving large amounts of data over the internet.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5971f448819090f6e76c7d3ffc2d |
completed | March 20, 2026, 2:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfa5a7aac8190b540b80816d55051 |
completed | March 21, 2026, 1:54 a.m. |
Created at: March 20, 2026, 1:11 p.m.