MOL
E1021592
MOL is the vehicle registration code used on license plates for the Märkisch-Oderland district in the German state of Brandenburg.
All labels observed (1)
| Label | Occurrences |
|---|---|
| MOL canonical | 6 |
How this entity was disambiguated
This entity first appeared as the object of triple T13114022 — 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: MOL Context triple: [Märkisch-Oderland, vehicleRegistrationCode, MOL]
-
A.
MOL Global
MOL Global was a Malaysian online payment solutions provider best known for acquiring the once-popular social networking site Friendster.
-
B.
Uniper
Uniper is a German energy company focused on power generation and global energy trading, formed from the conventional energy business spun off from E.ON.
-
C.
Neste Oil
Neste Oil was the former name of Neste, a Finnish energy company best known today for its production of renewable fuels and sustainable energy solutions.
-
D.
Ineos
Ineos is a large multinational chemicals and energy company based in the United Kingdom, known for its extensive portfolio of petrochemical, oil, gas, and manufacturing operations worldwide.
-
E.
Royal Vopak
Royal Vopak is a Dutch multinational tank storage company that specializes in storing and handling liquid bulk products such as chemicals, oil, gases, and biofuels at terminals worldwide.
- 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: MOL Target entity description: MOL is the vehicle registration code used on license plates for the Märkisch-Oderland district in the German state of Brandenburg.
-
A.
MOL Global
MOL Global was a Malaysian online payment solutions provider best known for acquiring the once-popular social networking site Friendster.
-
B.
Uniper
Uniper is a German energy company focused on power generation and global energy trading, formed from the conventional energy business spun off from E.ON.
-
C.
Neste Oil
Neste Oil was the former name of Neste, a Finnish energy company best known today for its production of renewable fuels and sustainable energy solutions.
-
D.
Ineos
Ineos is a large multinational chemicals and energy company based in the United Kingdom, known for its extensive portfolio of petrochemical, oil, gas, and manufacturing operations worldwide.
-
E.
Royal Vopak
Royal Vopak is a Dutch multinational tank storage company that specializes in storing and handling liquid bulk products such as chemicals, oil, gases, and biofuels at terminals worldwide.
- F. None of above. chosen
Statements (22)
| Predicate | Object |
|---|---|
| instanceOf |
German vehicle registration code
ⓘ
district of Brandenburg ⓘ license plate code ⓘ |
| abbreviationOf | Märkisch-Oderland ⓘ |
| category | Vehicle registration plates of Germany ⓘ |
| codeType | Kfz-Kennzeichen ⓘ |
| country | Germany ⓘ |
| countrySubdivision |
federal state of Brandenburg
ⓘ
linked to:
Brandenburg
|
| denotes |
Märkisch-Oderland district
ⓘ
linked to:
Märkisch-Oderland (district)
|
| introducedFor |
Märkisch-Oderland district
ⓘ
linked to:
Märkisch-Oderland (district)
|
| languageOfAbbreviation | German ⓘ |
| locatedIn |
Brandenburg
ⓘ
Federal Republic of Germany ⓘ
linked to:
Germany
|
| numberOfLetters | 3 ⓘ |
| regionType | Landkreis (rural district) ⓘ |
| usedInCountry | Germany ⓘ |
| usedInDistrict | Märkisch-Oderland ⓘ |
| usedInState | Brandenburg ⓘ |
| usedOn |
motor vehicle license plates
ⓘ
trailer license plates ⓘ |
| vehicleRegistrationCode | MOL ⓘ |
| writingSystem | Latin alphabet ⓘ |
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: MOL Description of subject: MOL is the vehicle registration code used on license plates for the Märkisch-Oderland district in the German state of Brandenburg.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.