MD
E656036
MD is the vehicle registration code used on license plates for the Austrian district of Mödling.
All labels observed (1)
| Label | Occurrences |
|---|---|
| MD canonical | 3 |
How this entity was disambiguated
This entity first appeared as the object of triple T7293118 — 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: MD Context triple: [Mödling, vehicleRegistrationCode, MD]
-
A.
MD
MD is the station code used to identify Maitland railway station in New South Wales, Australia.
-
B.
MD
MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
-
C.
MA
MA is the vehicle registration code used on license plates for the German city of Mannheim.
-
D.
MA
MA is the stock ticker symbol for Mastercard Incorporated, a leading global payments and financial services company.
-
E.
MA
MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
- 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: MD Target entity description: MD is the vehicle registration code used on license plates for the Austrian district of Mödling.
-
A.
MD
MD is the station code used to identify Maitland railway station in New South Wales, Australia.
-
B.
MD
MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
-
C.
MA
MA is the stock ticker symbol for Mastercard Incorporated, a leading global payments and financial services company.
-
D.
MA
MA is the vehicle registration code used on license plates for the German city of Mannheim.
-
E.
MA
MA is the two-letter ISO 3166-1 alpha-2 country code assigned to Morocco.
- F. None of above. chosen
Statements (15)
| Predicate | Object |
|---|---|
| instanceOf | vehicle registration code ⓘ |
| administrativeRegion | Lower Austria ⓘ |
| appliesTo |
motor vehicles
ⓘ
trailers ⓘ |
| codeType | geographic code ⓘ |
| country | Austria ⓘ |
| hasFormatRole | prefix on license plate ⓘ |
| identifiesRegistrationOffice | Mödling registration office ⓘ |
| introducedInCountry | Austria ⓘ |
| languageOfCode | Latin alphabet ⓘ |
| partOfSystem | Austrian vehicle registration plate system ⓘ |
| representsCity | Mödling ⓘ |
| representsDistrict | Mödling District ⓘ |
| usedByAuthority |
Austrian registration authorities
ⓘ
linked to:
Austrian federal authorities
|
| usedOn | vehicle 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: MD Description of subject: MD is the vehicle registration code used on license plates for the Austrian district of Mödling.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.