M
E35617
data transformation language
domain-specific language
functional programming language
query language
M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
All labels observed (1)
| Label | Occurrences |
|---|---|
| M canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T277324 — 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 Context triple: [Power BI, programmingLanguage, M]
-
A.
Ma
Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
-
B.
MP
MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
-
C.
J
J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
-
D.
S
S is the distinctive middle initial of U.S. President Harry S. Truman, famously not standing for any specific name but honoring both of his grandfathers.
-
E.
MC
MC is the official abbreviation for NATO’s highest military authority, the NATO Military Committee.
- 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 Target entity description: M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
-
A.
Ma
Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
-
B.
MP
MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
-
C.
J
J is a New York City Subway service that runs through Brooklyn and Queens into Manhattan, serving neighborhoods in eastern Brooklyn and southern Queens.
-
D.
S
S is the distinctive middle initial of U.S. President Harry S. Truman, famously not standing for any specific name but honoring both of his grandfathers.
-
E.
MC
MC is the official abbreviation for NATO’s highest military authority, the NATO Military Committee.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
data transformation language
ⓘ
domain-specific language ⓘ functional programming language ⓘ query language ⓘ |
| alsoKnownAs |
Power Query M
ⓘ
linked to:
Power Query
|
| canConnectTo |
files
ⓘ
online services ⓘ relational databases ⓘ web services ⓘ |
| designedFor |
business intelligence scenarios
ⓘ
data analysts ⓘ |
| developedBy | Microsoft ⓘ |
| executedBy |
Power Query engine
ⓘ
linked to:
Power Query
|
| hasFeature |
built-in library functions
ⓘ
custom connectors support ⓘ immutable values ⓘ lazy evaluation ⓘ let expressions ⓘ list types ⓘ record types ⓘ table types ⓘ type system ⓘ |
| inputFormat |
semi-structured data
ⓘ
structured data ⓘ |
| integratedWith |
Power BI Desktop
ⓘ
linked to:
Power BI
Power BI Service dataflows ⓘ |
| primaryUse | ETL in self-service BI ⓘ |
| programmingParadigm | functional ⓘ |
| supports |
column operations
ⓘ
custom functions ⓘ data aggregation ⓘ data cleansing ⓘ data filtering ⓘ data mashup ⓘ data preparation ⓘ data transformation ⓘ data type conversion ⓘ error handling ⓘ grouping ⓘ joins ⓘ query folding ⓘ row operations ⓘ |
| usedIn |
Azure Data Factory Power Query
ⓘ
linked to:
Power Query
Excel Power Query ⓘ
linked to:
Power Query
Microsoft Dataverse dataflows ⓘ Microsoft Excel Get & Transform Data ⓘ
linked to:
Power Query
Microsoft Power BI ⓘ
linked to:
Power BI
Power Query ⓘ SQL Server Analysis Services Tabular ⓘ |
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 Description of subject: M is a functional data mashup and query language used in Microsoft Power BI and related tools for data transformation and preparation.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.