HMS Royal Sovereign (05)
E748167
HMS Royal Sovereign (05) was a British Royal Navy Revenge-class battleship that served in both World Wars, noted for her role in Atlantic convoy escort and later service with the Soviet Navy as Arkhangelsk.
All labels observed (1)
| Label | Occurrences |
|---|---|
| HMS Royal Sovereign (05) canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8121027 — 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: HMS Royal Sovereign (05) Context triple: [Cammell Laird, built, HMS Royal Sovereign (05)]
-
A.
HMS Suffolk
HMS Suffolk was a British Royal Navy heavy cruiser of the County class that notably shadowed the German battleship Bismarck during World War II.
-
B.
HMS Superb
HMS Superb was a British Royal Navy warship noted for her service during the Napoleonic Wars, including distinguished action in major naval engagements.
-
C.
HMS Hampton Court
HMS Hampton Court was a Royal Navy warship that served in the British fleet during early 18th-century operations in the Caribbean, including actions around Porto Bello.
-
D.
HMS Legion
HMS Legion was a British Royal Navy L-class destroyer that served with distinction during World War II, notably in Mediterranean convoy and fleet operations.
-
E.
HMS Valiant
HMS Valiant was a British Royal Navy nuclear-powered fleet submarine of the Valiant class that served during the Cold War.
- 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: HMS Royal Sovereign (05) Target entity description: HMS Royal Sovereign (05) was a British Royal Navy Revenge-class battleship that served in both World Wars, noted for her role in Atlantic convoy escort and later service with the Soviet Navy as Arkhangelsk.
-
A.
HMS Suffolk
HMS Suffolk was a British Royal Navy heavy cruiser of the County class that notably shadowed the German battleship Bismarck during World War II.
-
B.
HMS Superb
HMS Superb was a British Royal Navy warship noted for her service during the Napoleonic Wars, including distinguished action in major naval engagements.
-
C.
HMS Hampton Court
HMS Hampton Court was a Royal Navy warship that served in the British fleet during early 18th-century operations in the Caribbean, including actions around Porto Bello.
-
D.
HMS Legion
HMS Legion was a British Royal Navy L-class destroyer that served with distinction during World War II, notably in Mediterranean convoy and fleet operations.
-
E.
HMS Valiant
HMS Valiant was a British Royal Navy nuclear-powered fleet submarine of the Valiant class that served during the Cold War.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
Revenge-class battleship
ⓘ
Royal Navy battleship ⓘ |
| armamentAA | various anti-aircraft guns (evolving over career) ⓘ |
| armamentMain | 8 × 15-inch (381 mm) guns in 4 twin turrets ⓘ |
| armamentSecondary | 6-inch guns ⓘ |
| armourBelt | up to about 13 inches ⓘ |
| armourConningTower | up to about 11 inches ⓘ |
| armourDeck | up to about 4 inches ⓘ |
| armourTurrets | up to about 13 inches ⓘ |
| beam | about 27 metres ⓘ |
| builder | Portsmouth Dockyard NERFINISHED ⓘ |
| class | Revenge class NERFINISHED ⓘ |
| commissioned | May 1916 ⓘ |
| conflict |
World War I
ⓘ
World War II ⓘ |
| country | United Kingdom ⓘ |
| crewComplement | around 900–1,200 officers and men ⓘ |
| displacementFullLoad | about 31,000 long tons ⓘ |
| displacementStandard | about 28,000 long tons ⓘ |
| draught | about 9.3 metres ⓘ |
| fate | scrapped ⓘ |
| laidDown | 15 January 1914 ⓘ |
| launched | 29 April 1915 ⓘ |
| length | about 189.8 metres ⓘ |
| maximumSpeed | about 21 knots ⓘ |
| navalEnsign | White Ensign NERFINISHED ⓘ |
| notableTheatre |
Arctic Ocean
NERFINISHED
ⓘ
Atlantic Ocean NERFINISHED ⓘ |
| operator |
Royal Navy
ⓘ
Soviet Navy NERFINISHED ⓘ |
| pennantNumber | 05 ⓘ |
| powerOutput | about 40,000 shaft horsepower ⓘ |
| propulsion |
coal-fired boilers (later oil-fired)
ⓘ
steam turbines ⓘ |
| range | about 7,000 nautical miles at 10 knots ⓘ |
| returnedFromSovietUnion | 1949 ⓘ |
| role |
Arctic convoy escort
ⓘ
Atlantic convoy escort ⓘ home fleet battleship ⓘ |
| scrappedIn | 1950 ⓘ |
| servedAs | Arkhangelsk in Soviet Navy ⓘ |
| serviceEntry | 1916 ⓘ |
| sisterShip |
HMS Ramillies
NERFINISHED
ⓘ
HMS Resolution NERFINISHED ⓘ HMS Revenge NERFINISHED ⓘ HMS Royal Oak NERFINISHED ⓘ |
| SovietName | Arkhangelsk NERFINISHED ⓘ |
| transferDate | 1944 ⓘ |
| transferredTo | Soviet Union NERFINISHED ⓘ |
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: HMS Royal Sovereign (05) Description of subject: HMS Royal Sovereign (05) was a British Royal Navy Revenge-class battleship that served in both World Wars, noted for her role in Atlantic convoy escort and later service with the Soviet Navy as Arkhangelsk.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.