M language
E188108
data mashup language
data transformation language
domain-specific language
functional programming language
M language is a functional, case-sensitive data mashup and transformation language used primarily in Microsoft Power Query for importing, shaping, and combining data from diverse sources.
All labels observed (1)
| Label | Occurrences |
|---|---|
| M language canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T1668833 — 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: M language Context triple: [Power Query, hasComponent, M language]
-
A.
Mono language
Mono language is a Native American Uto-Aztecan language traditionally spoken by the Mono people of eastern California.
-
B.
Microsoft Intermediate Language
Microsoft Intermediate Language is the low-level, platform-independent bytecode used by the .NET Framework’s Common Language Runtime as the compilation target for .NET languages before just-in-time compilation to native machine code.
-
C.
F#
F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
-
D.
M-Code
M-Code is an advanced, encrypted military GPS signal designed to provide more secure and jam-resistant positioning and navigation for authorized users.
-
E.
.NET languages
.NET languages are a family of programming languages, such as C#, F#, and Visual Basic .NET, designed to run on the Microsoft .NET platform and share a common runtime and libraries.
- 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: M language Target entity description: M language is a functional, case-sensitive data mashup and transformation language used primarily in Microsoft Power Query for importing, shaping, and combining data from diverse sources.
-
A.
Mono language
Mono language is a Native American Uto-Aztecan language traditionally spoken by the Mono people of eastern California.
-
B.
Microsoft Intermediate Language
Microsoft Intermediate Language is the low-level, platform-independent bytecode used by the .NET Framework’s Common Language Runtime as the compilation target for .NET languages before just-in-time compilation to native machine code.
-
C.
F#
F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
-
D.
M-Code
M-Code is an advanced, encrypted military GPS signal designed to provide more secure and jam-resistant positioning and navigation for authorized users.
-
E.
.NET languages
.NET languages are a family of programming languages, such as C#, F#, and Visual Basic .NET, designed to run on the Microsoft .NET platform and share a common runtime and libraries.
- F. None of above. chosen
Statements (56)
| Predicate | Object |
|---|---|
| instanceOf |
data mashup language
ⓘ
data transformation language ⓘ domain-specific language ⓘ functional programming language ⓘ |
| allows | editing queries via Advanced Editor in Power Query ⓘ |
| alsoKnownAs |
Power Query M
ⓘ
linked to:
Power Query
Power Query M formula language ⓘ
linked to:
Power Query
|
| dataModel | based on values, lists, records, and tables ⓘ |
| developedBy | Microsoft ⓘ |
| documentationHostedAt | Microsoft Learn ⓘ |
| evaluationStrategy | lazy evaluation with query folding to data sources ⓘ |
| executionModel | query-based ⓘ |
| hasFeature |
automatic type detection
ⓘ
built-in data type conversion ⓘ lazy evaluation semantics ⓘ native support for CSV ⓘ native support for Excel workbooks ⓘ native support for JSON ⓘ native support for OData feeds ⓘ native support for XML ⓘ native support for relational databases ⓘ native support for text files ⓘ native support for web data sources ⓘ rich library of data connectors ⓘ step-based query definition ⓘ |
| integratedWith | Power Query user interface ⓘ |
| isCaseSensitive | true ⓘ |
| isTuringComplete | true ⓘ |
| officialName |
Power Query Formula Language
ⓘ
linked to:
Power Query
|
| paradigm | functional ⓘ |
| primaryPurpose |
combining data
ⓘ
data mashup ⓘ data transformation ⓘ importing data from diverse sources ⓘ shaping data ⓘ |
| supports |
custom functions
ⓘ
error handling with try expression ⓘ function types ⓘ higher-order functions ⓘ immutable values ⓘ let expressions ⓘ list types ⓘ pattern-based data transformation ⓘ query folding ⓘ record types ⓘ table types ⓘ type annotations ⓘ |
| syntaxStyle | expression-based ⓘ |
| typeSystem | static with gradual typing characteristics ⓘ |
| usedIn |
Azure Data Factory Power Query activity
ⓘ
linked to:
Power Query
Dataflows in Power Apps ⓘ
linked to:
Microsoft Dataverse dataflows
Dataflows in Power BI ⓘ
linked to:
Power BI Service dataflows
Excel Power Query ⓘ
linked to:
Power Query
Microsoft Power Query ⓘ
linked to:
Power Query
Power BI Desktop ⓘ
linked to:
Power BI Desktop (Report Server optimized)
Power Query Online ⓘ
linked to:
Power Query
|
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: M language Description of subject: M language is a functional, case-sensitive data mashup and transformation language used primarily in Microsoft Power Query for importing, shaping, and combining data from diverse sources.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.