Niño 3.4 index
E21753
The Niño 3.4 index is a climate indicator that tracks sea surface temperature anomalies in a central equatorial Pacific region to quantify the strength and phase of El Niño and La Niña events.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Niño 3.4 index canonical | 2 |
| Niño 1+2 index | 1 |
| Niño 3 index | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T174465 — 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: Niño 3.4 index Context triple: [El Niño–Southern Oscillation, isMeasuredBy, Niño 3.4 index]
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A.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
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B.
Jimintō
Jimintō is the dominant conservative political party in Japan, formally known as the Liberal Democratic Party.
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C.
DNI
DNI is the commonly used acronym for the Director of National Intelligence, the head of the U.S. intelligence community.
-
D.
Nielson
Nielson is a surname and given name that functions as a spelling variant of Nelson, commonly of Scandinavian or English origin.
-
E.
Tverya
Tverya is the Hebrew name for Tiberias, an ancient city in northern Israel on the western shore of the Sea of Galilee known for its religious significance and hot springs.
- 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: Niño 3.4 index Target entity description: The Niño 3.4 index is a climate indicator that tracks sea surface temperature anomalies in a central equatorial Pacific region to quantify the strength and phase of El Niño and La Niña events.
-
A.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
-
B.
Jimintō
Jimintō is the dominant conservative political party in Japan, formally known as the Liberal Democratic Party.
-
C.
DNI
DNI is the commonly used acronym for the Director of National Intelligence, the head of the U.S. intelligence community.
-
D.
Nielson
Nielson is a surname and given name that functions as a spelling variant of Nelson, commonly of Scandinavian or English origin.
-
E.
Tverya
Tverya is the Hebrew name for Tiberias, an ancient city in northern Israel on the western shore of the Sea of Galilee known for its religious significance and hot springs.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
El Niño–Southern Oscillation index
ⓘ
climate index ⓘ sea surface temperature anomaly index ⓘ |
| appliedIn |
agricultural planning
ⓘ
disaster risk management related to ENSO ⓘ hydrological forecasting ⓘ |
| basedOn |
sea surface temperature
ⓘ
sea surface temperature anomalies relative to a climatological mean ⓘ |
| commonlyComputedAs | 3-month running mean of sea surface temperature anomalies ⓘ |
| correlatesWith |
changes in atmospheric circulation patterns
ⓘ
global temperature anomalies ⓘ precipitation anomalies in the tropics ⓘ shifts in tropical convection ⓘ |
| dataSource | sea surface temperature analyses from observational and reanalysis products ⓘ |
| definedOverRegion | Niño 3.4 region ⓘ |
| helpsCharacterize | teleconnections between the tropical Pacific and global climate ⓘ |
| maintainedBy |
Climate Prediction Center
ⓘ
surface form:
NOAA Climate Prediction Center
National Oceanic and Atmospheric Administration ⓘ |
| measures | sea surface temperature anomalies in the central equatorial Pacific Ocean ⓘ |
| quantifies |
ENSO intensity
ⓘ
cold phase of ENSO ⓘ warm phase of ENSO ⓘ |
| regionLatitudeRange | 5°N to 5°S ⓘ |
| regionLongitudeRange | 170°W to 120°W ⓘ |
| relatedTo |
Niño 3.4 index
self-linksurface differs
ⓘ
surface form:
Niño 1+2 index
Niño 3.4 index self-linksurface differs ⓘ
surface form:
Niño 3 index
Niño 4 index ⓘ Oceanic Niño Index ⓘ Southern Oscillation Index ⓘ |
| spatialDomain | central equatorial Pacific Ocean ⓘ |
| thresholdConvention |
El Niño
ⓘ
surface form:
El Niño often defined when anomalies exceed about +0.5 °C for several consecutive overlapping seasons
La Niña ⓘ
surface form:
La Niña often defined when anomalies are below about −0.5 °C for several consecutive overlapping seasons
|
| timeResolution |
monthly
ⓘ
seasonal ⓘ |
| tracks | sea surface temperature anomalies ⓘ |
| typicalBaselinePeriod | 30-year climatological period ⓘ |
| unit | degrees Celsius ⓘ |
| usedBy |
climate scientists
ⓘ
meteorological agencies ⓘ operational forecasting centers ⓘ |
| usedFor |
assessing global climate variability
ⓘ
determining the phase of the El Niño–Southern Oscillation ⓘ monitoring ENSO conditions ⓘ quantifying the strength of El Niño events ⓘ quantifying the strength of La Niña events ⓘ seasonal climate prediction ⓘ |
| usedToDefine |
El Niño conditions
ⓘ
La Niña conditions ⓘ |
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: Niño 3.4 index Description of subject: The Niño 3.4 index is a climate indicator that tracks sea surface temperature anomalies in a central equatorial Pacific region to quantify the strength and phase of El Niño and La Niña events.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Niño 3 index
this entity surface form:
Niño 1+2 index