Sea, Lake, and Overland Surges from Hurricanes model
E237737
The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is a computer simulation tool developed by the U.S. National Weather Service to estimate storm surge heights and inundation from tropical cyclones for coastal emergency planning and forecasting.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Sea, Lake, and Overland Surges from Hurricanes model canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2121306 — 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: Sea, Lake, and Overland Surges from Hurricanes model Context triple: [Storm Surge Unit, usesModel, Sea, Lake, and Overland Surges from Hurricanes model]
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A.
Storm Surge Unit
The Storm Surge Unit is a specialized division of the National Hurricane Center that analyzes and forecasts coastal flooding risks associated with tropical cyclones and other storm events.
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B.
Atlantic coastal defenses of Puerto Rico
The Atlantic coastal defenses of Puerto Rico comprise the historic fortifications, walls, and military structures built primarily by the Spanish Empire to protect the island’s northern coastline and the strategic port of San Juan from seaborne attacks.
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C.
Saffir–Simpson Hurricane Wind Scale
The Saffir–Simpson Hurricane Wind Scale is a 1-to-5 categorization system that rates hurricanes based on their sustained wind speeds and potential for property damage.
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D.
Hurricane Sandy flooding in 2012
Hurricane Sandy flooding in 2012 was a devastating storm surge and inundation event along the U.S. East Coast that caused widespread damage, power outages, and displacement in coastal communities.
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E.
Hurricane Specialist Unit
The Hurricane Specialist Unit is the team of expert meteorologists at the National Hurricane Center responsible for forecasting, tracking, and issuing warnings for tropical cyclones.
- 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: Sea, Lake, and Overland Surges from Hurricanes model Target entity description: The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is a computer simulation tool developed by the U.S. National Weather Service to estimate storm surge heights and inundation from tropical cyclones for coastal emergency planning and forecasting.
-
A.
Storm Surge Unit
The Storm Surge Unit is a specialized division of the National Hurricane Center that analyzes and forecasts coastal flooding risks associated with tropical cyclones and other storm events.
-
B.
Atlantic coastal defenses of Puerto Rico
The Atlantic coastal defenses of Puerto Rico comprise the historic fortifications, walls, and military structures built primarily by the Spanish Empire to protect the island’s northern coastline and the strategic port of San Juan from seaborne attacks.
-
C.
Saffir–Simpson Hurricane Wind Scale
The Saffir–Simpson Hurricane Wind Scale is a 1-to-5 categorization system that rates hurricanes based on their sustained wind speeds and potential for property damage.
-
D.
Hurricane Sandy flooding in 2012
Hurricane Sandy flooding in 2012 was a devastating storm surge and inundation event along the U.S. East Coast that caused widespread damage, power outages, and displacement in coastal communities.
-
E.
Hurricane Specialist Unit
The Hurricane Specialist Unit is the team of expert meteorologists at the National Hurricane Center responsible for forecasting, tracking, and issuing warnings for tropical cyclones.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
computer simulation tool
ⓘ
numerical model ⓘ storm surge model ⓘ |
| abbreviation | SLOSH model ⓘ |
| appliesTo |
coastal regions
ⓘ
hurricanes ⓘ tropical cyclones ⓘ |
| basedOn | shallow-water equations ⓘ |
| considers |
coastal bathymetry
ⓘ
coastal topography ⓘ landfall angle of storm ⓘ storm size and structure ⓘ |
| countryOfOrigin |
United States of America
ⓘ
surface form:
United States
|
| developer |
National Oceanic and Atmospheric Administration
ⓘ
National Weather Service ⓘ
surface form:
U.S. National Weather Service
|
| domain |
coastal engineering
ⓘ
meteorology ⓘ oceanography ⓘ |
| hasAcronym | SLOSH ⓘ |
| input |
astronomical tide level
ⓘ
bathymetry ⓘ coastline geometry ⓘ forward speed of storm ⓘ storm intensity ⓘ storm landfall location ⓘ storm size ⓘ storm track ⓘ topography ⓘ |
| output |
inundation extent maps
ⓘ
maximum envelope of water ⓘ storm surge height ⓘ storm surge inundation depth ⓘ |
| partOf | U.S. hurricane forecast and warning system ⓘ |
| simulates |
pressure-driven water level changes
ⓘ
wind-driven water level changes ⓘ |
| supports | storm surge watch and warning products ⓘ |
| use |
coastal emergency planning
ⓘ
estimate storm surge heights ⓘ estimate storm surge inundation ⓘ evacuation planning ⓘ hazard assessment ⓘ tropical cyclone storm surge forecasting ⓘ |
| usedBy |
National Hurricane Center
ⓘ
coastal planners ⓘ emergency managers ⓘ |
| usedFor |
hurricane evacuation zone design
ⓘ
operational storm surge guidance ⓘ risk communication ⓘ |
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: Sea, Lake, and Overland Surges from Hurricanes model Description of subject: The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is a computer simulation tool developed by the U.S. National Weather Service to estimate storm surge heights and inundation from tropical cyclones for coastal emergency planning and forecasting.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.