DataSet API
E711832
DataSet API is Apache Flink’s now-legacy batch processing API for defining and executing scalable, distributed data transformations.
All labels observed (1)
| Label | Occurrences |
|---|---|
| DataSet API canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8093951 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DataSet API Context triple: [Apache Flink, hasAPI, DataSet API]
-
A.
DataView
DataView is ML.NET’s core, schema-aware tabular data abstraction used to efficiently represent and process datasets for machine learning pipelines.
-
B.
Data
Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
-
C.
OS OpenData
OS OpenData is a collection of free, publicly available digital mapping and geographic datasets released by Ordnance Survey for use in analysis, applications, and research.
-
D.
Ecdat
Ecdat is a term most likely associated with the name of Ecdat Park, suggesting it is a proper noun used in geographic or place naming.
-
E.
Open Data Index
Open Data Index is a global initiative that evaluates and ranks the openness and accessibility of government data across countries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DataSet API Target entity description: DataSet API is Apache Flink’s now-legacy batch processing API for defining and executing scalable, distributed data transformations.
-
A.
DataView
DataView is ML.NET’s core, schema-aware tabular data abstraction used to efficiently represent and process datasets for machine learning pipelines.
-
B.
Data
Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
-
C.
OS OpenData
OS OpenData is a collection of free, publicly available digital mapping and geographic datasets released by Ordnance Survey for use in analysis, applications, and research.
-
D.
Ecdat
Ecdat is a term most likely associated with the name of Ecdat Park, suggesting it is a proper noun used in geographic or place naming.
-
E.
Open Data Index
Open Data Index is a global initiative that evaluates and ranks the openness and accessibility of government data across countries.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
Apache Flink API
ⓘ
batch processing API ⓘ |
| category |
big data framework API
ⓘ
data-parallel programming API ⓘ |
| designedFor |
fault-tolerant processing
ⓘ
scalable processing ⓘ |
| developer | Apache Flink community ⓘ |
| documentationURL | https://nightlies.apache.org/flink/flink-docs-stable/dev/batch ⓘ |
| ecosystem |
Apache Flink stack
ⓘ
linked to:
Apache Flink
|
| executionEngine | Flink batch runtime ⓘ |
| executionModel | distributed ⓘ |
| feature |
custom partitioning
ⓘ
grouping and aggregation ⓘ iterations ⓘ joins ⓘ operators like map, flatMap, filter, reduce ⓘ support for user-defined functions ⓘ type-safe transformations ⓘ |
| inputFormat |
HDFS
ⓘ
collections ⓘ files ⓘ |
| integratesWith | Flink runtime ⓘ |
| license | Apache License 2.0 ⓘ |
| notDesignedFor | unbounded streaming data ⓘ |
| outputFormat |
HDFS
ⓘ
files ⓘ |
| partOf | Apache Flink ⓘ |
| programmingLanguage |
Java
ⓘ
Scala ⓘ |
| relation | predecessor of unified Flink APIs for batch and streaming ⓘ |
| replacedBy |
Flink DataStream API
ⓘ
linked to:
DataStream API
Flink Table API ⓘ
linked to:
Table API
|
| scope | bounded data ⓘ |
| status | legacy ⓘ |
| supports |
batch processing
ⓘ
data transformations ⓘ distributed data processing ⓘ |
| supportsOptimization |
automatic execution plan optimization
ⓘ
data pipelining ⓘ operator chaining ⓘ |
| targetUser |
Java developers
ⓘ
Scala developers ⓘ big data engineers ⓘ data engineers ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: DataSet API Description of subject: DataSet API is Apache Flink’s now-legacy batch processing API for defining and executing scalable, distributed data transformations.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.