Triple
T17561298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pub/Sub Lite |
E427700
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | managed streaming data service |
C23352
|
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: managed streaming data service Context triple: [Pub/Sub Lite, instanceOf, managed streaming data service]
-
A.
managed data ingestion service
A managed data ingestion service is a fully hosted platform that reliably collects, transforms, and routes data from diverse sources into target systems at scale, handling infrastructure, scaling, and monitoring automatically.
-
B.
data streaming platform
chosen
A data streaming platform is a system that enables the continuous ingestion, processing, and delivery of real-time data streams between producers and consumers at scale.
-
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.
data transfer service
A data transfer service is a system that securely and efficiently moves data between different locations, systems, or applications, often handling scheduling, reliability, and format compatibility.
-
E.
managed message queuing service
A managed message queuing service is a cloud-based system that reliably receives, stores, and delivers messages between distributed application components, handling scalability, durability, and operational maintenance automatically.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.