Triple
T17499436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS Management and Governance services |
E426153
|
entity |
| Predicate | includesService |
P1393
|
FINISHED |
| Object | AWS Compute Optimizer |
—
|
NE NERFINISHED |
How this triple was built (3 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 Compute Optimizer | Statement: [AWS Management and Governance services, includesService, AWS Compute Optimizer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AWS Compute Optimizer Context triple: [AWS Management and Governance services, includesService, AWS Compute Optimizer]
-
A.
AWS Auto Scaling
AWS Auto Scaling is an Amazon Web Services feature that automatically adjusts the number of compute resources in response to changing application demand to maintain performance and optimize costs.
-
B.
Azure Savings Plan for Compute
Azure Savings Plan for Compute is a flexible pricing offering from Microsoft Azure that lets customers reduce costs on compute services by committing to a consistent hourly spend over a one- or three-year term.
-
C.
Amazon Web Services Graviton processors
Amazon Web Services Graviton processors are custom AWS-designed, cloud-optimized server CPUs that deliver high performance and energy efficiency for a wide range of workloads.
-
D.
Azure Advisor
Azure Advisor is a cloud optimization service that analyzes your Azure resources and provides personalized recommendations to improve cost efficiency, performance, reliability, and security.
-
E.
Amazon EC2
Amazon EC2 is a scalable cloud computing service that provides virtual servers (instances) for running applications on Amazon Web Services infrastructure.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AWS Compute Optimizer Target entity description: AWS Compute Optimizer is an Amazon Web Services tool that analyzes resource usage to recommend optimal compute configurations for cost savings and performance improvements.
-
A.
AWS Auto Scaling
AWS Auto Scaling is an Amazon Web Services feature that automatically adjusts the number of compute resources in response to changing application demand to maintain performance and optimize costs.
-
B.
Azure Savings Plan for Compute
Azure Savings Plan for Compute is a flexible pricing offering from Microsoft Azure that lets customers reduce costs on compute services by committing to a consistent hourly spend over a one- or three-year term.
-
C.
Amazon Web Services Graviton processors
Amazon Web Services Graviton processors are custom AWS-designed, cloud-optimized server CPUs that deliver high performance and energy efficiency for a wide range of workloads.
-
D.
Azure Advisor
Azure Advisor is a cloud optimization service that analyzes your Azure resources and provides personalized recommendations to improve cost efficiency, performance, reliability, and security.
-
E.
Amazon EC2
Amazon EC2 is a scalable cloud computing service that provides virtual servers (instances) for running applications on Amazon Web Services infrastructure.
- F. None of above. chosen
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452112ff0819089c2951baba90102 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.