Triple
T32473730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secondary NameNode |
E829911
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | HDFS component |
C57948
|
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: HDFS component Context triple: [Secondary NameNode, instanceOf, HDFS component]
-
A.
component of Apache Hive
A component of Apache Hive is a modular subsystem—such as the metastore, query engine, or storage handler—that collaborates with other parts of Hive to translate, optimize, and execute SQL-like queries over distributed data.
-
B.
Apache Flink component
An Apache Flink component is a modular building block within a Flink-based data processing pipeline that performs specific tasks such as data ingestion, transformation, state management, or output to sinks in both batch and stream processing applications.
-
C.
ZFS component
A ZFS component is an individual module or subsystem within the ZFS storage stack that contributes specific functionality such as data integrity, pooling, caching, or snapshot management.
-
D.
Flink component
A Flink component is a modular building block within an Apache Flink application that performs a specific function in the data processing pipeline, such as sourcing, transforming, or sinking streaming or batch data.
-
E.
component of Apache Storm
A component of Apache Storm is a modular processing unit—such as a spout or bolt—that participates in a real-time, distributed computation topology by emitting, transforming, or aggregating streaming data tuples.
- 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:57 a.m.