Triple
T15989636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloudera |
E387790
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Cloudera DataFlow |
E387790
|
NE FINISHED |
How this triple was built (2 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: Cloudera DataFlow | Statement: [Cloudera, product, Cloudera DataFlow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cloudera DataFlow Context triple: [Cloudera, product, Cloudera DataFlow]
-
A.
Cloudera
chosen
Cloudera is an enterprise data management and analytics company best known for its platform built on Apache Hadoop and related open-source big data technologies.
-
B.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
C.
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
D.
IBM Streams
IBM Streams is a high-performance stream processing platform that enables real-time ingestion, analysis, and correlation of large-scale data in motion for enterprise applications.
-
E.
Apache NiFi
Apache NiFi is an open-source data integration and flow automation tool designed to manage, route, and transform data between disparate systems in real time.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157829ec08190aa4a683e29a0148a |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3d2369081909efa2d4addf0cf2d |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:54 a.m.