Triple
T27591631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitess |
E699799
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cloud-native database technology |
C23261
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: cloud-native database technology Context triple: [Vitess, instanceOf, cloud-native database technology]
-
A.
cloud-native application
A cloud-native application is a software system designed and built specifically to run in cloud environments, leveraging microservices, containers, dynamic orchestration, and continuous delivery to achieve scalability, resilience, and rapid iteration.
-
B.
cloud native project
chosen
A cloud native project is an application or system designed, built, and operated to fully leverage cloud computing models—such as containerization, microservices, dynamic orchestration, and managed services—for scalability, resilience, and rapid delivery.
-
C.
managed database service
A managed database service is a cloud-based offering where the provider handles database setup, maintenance, scaling, backups, and security, allowing users to focus on using the data rather than managing the infrastructure.
-
D.
NoSQL database
A NoSQL database is a non-relational data storage system designed to handle large volumes of diverse, rapidly changing data with flexible schemas and horizontal scalability.
-
E.
database service provider
A database service provider is an entity that offers infrastructure, tools, and managed services for storing, organizing, securing, and accessing data in databases for clients or applications.
- F. None of above.
Provenance (1 batch)
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_69ef6a4d71f081909a1235763206b691 |
completed | April 27, 2026, 1:53 p.m. |
Created at: April 27, 2026, 2:05 p.m.