MA
E613798
MA is the vehicle registration code used on license plates for the German city of Mannheim.
All labels observed (1)
| Label | Occurrences |
|---|---|
| MA canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T6708914 — 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: MA Context triple: [Mannheim, vehicleRegistrationCode, MA]
-
A.
MA
MA is the stock ticker symbol for Mastercard Incorporated, a leading global payments and financial services company.
-
B.
MA
MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
-
C.
Ma
Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
-
D.
Ma
Ma is a 2019 psychological horror film starring Octavia Spencer as a lonely woman who befriends a group of teenagers with increasingly disturbing consequences.
-
E.
MN
MN is the vehicle registration code used on license plates for vehicles registered in Douglas and the rest of the Isle of Man.
- 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: MA Target entity description: MA is the vehicle registration code used on license plates for the German city of Mannheim.
-
A.
MA
MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
-
B.
MA
MA is the stock ticker symbol for Mastercard Incorporated, a leading global payments and financial services company.
-
C.
Ma
Ma is a common Chinese surname borne by many notable individuals across fields such as music, politics, and sports.
-
D.
Ma
Ma is a 2019 psychological horror film starring Octavia Spencer as a lonely woman who befriends a group of teenagers with increasingly disturbing consequences.
-
E.
MN
MN is the vehicle registration code used on license plates for vehicles registered in Douglas and the rest of the Isle of Man.
- F. None of above. chosen
Statements (20)
| Predicate | Object |
|---|---|
| instanceOf |
German vehicle registration code
ⓘ
city ⓘ vehicle registration code ⓘ |
| appliesTo |
motor vehicles
ⓘ
trailers ⓘ |
| assignedToCity | Mannheim ⓘ |
| cityLocatedInCountry | Germany ⓘ |
| cityLocatedInState | Baden-Württemberg ⓘ |
| codeType |
Kfz-Kennzeichen
ⓘ
car registration code ⓘ |
| countryCodeSystem | German vehicle registration system ⓘ |
| hasVehicleRegistrationCode | MA ⓘ |
| locatedIn |
Baden-Württemberg
ⓘ
Germany ⓘ |
| partOf | German vehicle registration plate system ⓘ |
| refersTo | Mannheim ⓘ |
| registrationCodeFor | Mannheim ⓘ |
| usedInCountry | Germany ⓘ |
| usedInState | Baden-Württemberg ⓘ |
| usedOn | license plates ⓘ |
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: MA Description of subject: MA is the vehicle registration code used on license plates for the German city of Mannheim.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject linked to:
Marbella, Andalusia, Spain