Triple
T27911796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM watsonx.data |
E705946
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cloud-native data store |
C53529
|
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 data store Context triple: [IBM watsonx.data, instanceOf, cloud-native data store]
-
A.
distributed storage engine
A distributed storage engine is a system that manages and coordinates data storage across multiple networked nodes to provide scalable, fault-tolerant, and high-performance data access.
-
B.
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.
-
C.
managed in-memory data store service
A managed in-memory data store service is a cloud-based solution that provides fast, scalable, and fully administered in-memory caching and data storage capabilities without requiring users to manage underlying infrastructure.
-
D.
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.
-
E.
cloud native project
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.
- F. None of above. chosen
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_69ef96b5aad08190be36a277c31e7004 |
completed | April 27, 2026, 5:02 p.m. |
Created at: April 27, 2026, 6:50 p.m.