Triple
T15989634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloudera |
E387790
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Cloudera Data Engineering |
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 Data Engineering | Statement: [Cloudera, product, Cloudera Data Engineering]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cloudera Data Engineering Context triple: [Cloudera, product, Cloudera Data Engineering]
-
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.
Google Cloud Dataproc
Google Cloud Dataproc is a managed cloud service for running Apache Hadoop, Spark, and other big data workloads on scalable, automated clusters in Google Cloud.
-
C.
CDH
CDH is the College of Humanities at EPFL, responsible for teaching and research in human and social sciences within the Swiss engineering and technology university.
-
D.
CDH
CDH is a centrist Christian democratic political party in Belgium, primarily active in the French-speaking region.
-
E.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
- 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.