Table API
E711833
Table API is Apache Flink’s high-level, declarative interface for expressing data processing and analytics using relational-style operations on streaming and batch data.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Apache Flink Table API | 1 |
| Flink Table API | 1 |
| Table API canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8093952 — 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: Table API Context triple: [Apache Flink, hasAPI, Table API]
-
A.
Tabularium
The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
-
B.
Tabular Editor
Tabular Editor is a specialized development tool for creating, managing, and optimizing tabular models used in platforms like Azure Analysis Services and Power BI.
-
C.
Table Table
Table Table is a UK-based casual dining pub-restaurant chain known for serving classic British comfort food, often located alongside Premier Inn hotels.
-
D.
tabla
The tabla is a pair of hand-played drums central to North Indian classical and folk music, known for its complex rhythms and tonal versatility.
-
E.
Tableau
Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
- 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: Table API Target entity description: Table API is Apache Flink’s high-level, declarative interface for expressing data processing and analytics using relational-style operations on streaming and batch data.
-
A.
Tabularium
The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
-
B.
Tabular Editor
Tabular Editor is a specialized development tool for creating, managing, and optimizing tabular models used in platforms like Azure Analysis Services and Power BI.
-
C.
Table Table
Table Table is a UK-based casual dining pub-restaurant chain known for serving classic British comfort food, often located alongside Premier Inn hotels.
-
D.
tabla
The tabla is a pair of hand-played drums central to North Indian classical and folk music, known for its complex rhythms and tonal versatility.
-
E.
Tableau
Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
Apache Flink component
ⓘ
data processing API ⓘ high-level API ⓘ |
| abstractionLevel | high-level ⓘ |
| allows |
definition of queries on batch data
ⓘ
definition of queries on streams ⓘ |
| belongsToProject | Apache Software Foundation ⓘ |
| dataModel |
dynamic tables
ⓘ
tables ⓘ |
| designedFor | unified batch and streaming processing ⓘ |
| developer |
Apache Flink community
ⓘ
linked to:
Apache Flink
|
| documentationURL | https://nightlies.apache.org/flink/flink-docs-stable/docs/dev/table ⓘ |
| executionModel | distributed ⓘ |
| integratesWith |
Flink DataStream API
ⓘ
linked to:
DataStream API
Flink runtime ⓘ |
| languageBinding |
Java
ⓘ
Python ⓘ Scala ⓘ |
| license | Apache License 2.0 ⓘ |
| partOf | Apache Flink ⓘ |
| programmingModel | declarative ⓘ |
| supports |
SQL-like operations
ⓘ
batch processing ⓘ batch-style bounded queries ⓘ data analytics ⓘ declarative data processing ⓘ event-time semantics ⓘ processing-time semantics ⓘ relational-style operations ⓘ stream processing ⓘ streaming-style unbounded queries ⓘ |
| supportsFeature |
catalog integration
ⓘ
connector-based I/O ⓘ grouping and aggregation ⓘ joins ⓘ schema definition ⓘ time-based operations ⓘ user-defined functions ⓘ windowing ⓘ |
| supportsOptimization | query optimization via Flink planner ⓘ |
| targetUser |
data analysts
ⓘ
data engineers ⓘ stream processing developers ⓘ |
| usedWith |
Apache Flink SQL
ⓘ
linked to:
Apache Flink
|
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: Table API Description of subject: Table API is Apache Flink’s high-level, declarative interface for expressing data processing and analytics using relational-style operations on streaming and batch data.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Table API