LISS-I
E898966
LISS-I is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
All labels observed (1)
| Label | Occurrences |
|---|---|
| LISS-I canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T11001858 — 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.
Target entity: LISS-I Context triple: [IRS-1B, primaryInstrument, LISS-I]
-
A.
LSS
LSS is the station code for LaSalle Street Station, a major commuter rail terminal in downtown Chicago, Illinois.
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B.
LI
LI is the Roman numeral representing the number 51.
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C.
LI
LI is the two-letter ISO 3166-1 alpha-2 country code for Liechtenstein.
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D.
LSL
LSL is the currency code for the Lesotho loti, the official monetary unit of Lesotho.
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E.
LIS
LIS is the three-letter IATA airport code for Humberto Delgado Airport, the main international airport serving Lisbon, Portugal.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: LISS-I Target entity description: LISS-I is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
-
A.
LSS
LSS is the station code for LaSalle Street Station, a major commuter rail terminal in downtown Chicago, Illinois.
-
B.
LI
LI is the Roman numeral representing the number 51.
-
C.
LI
LI is the two-letter ISO 3166-1 alpha-2 country code for Liechtenstein.
-
D.
LSL
LSL is the currency code for the Lesotho loti, the official monetary unit of Lesotho.
-
E.
LIS
LIS is the three-letter IATA airport code for Humberto Delgado Airport, the main international airport serving Lisbon, Portugal.
- F. None of above. chosen
Statements (28)
| Predicate | Object |
|---|---|
| instanceOf |
Earth observation instrument
ⓘ
multispectral imaging sensor ⓘ |
| application |
agriculture monitoring
ⓘ
environmental monitoring ⓘ land-cover mapping ⓘ land-use mapping ⓘ natural resources management ⓘ |
| countryOfOrigin | India ⓘ |
| dataType | Earth observation data ⓘ |
| dataUse |
crop area estimation
ⓘ
drought assessment ⓘ thematic mapping ⓘ water resources assessment ⓘ |
| hostMission |
IRS-1A Earth observation mission
ⓘ
IRS-1B Earth observation mission NERFINISHED ⓘ |
| missionFamily | IRS-1 series NERFINISHED ⓘ |
| operationalStatus | retired ⓘ |
| operator | Indian Space Research Organisation ⓘ |
| platformType | sun-synchronous satellite ⓘ |
| spatialResolutionCategory | medium resolution ⓘ |
| spectralBands |
near infrared
ⓘ
visible ⓘ |
| spectralType | multispectral ⓘ |
| successor |
LISS-II
NERFINISHED
ⓘ
LISS-III NERFINISHED ⓘ |
| usedOn |
IRS-1A
NERFINISHED
ⓘ
IRS-1B NERFINISHED ⓘ Indian Remote Sensing satellites 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.
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.
Subject: LISS-I Description of subject: LISS-I is a multispectral imaging sensor used on early Indian Remote Sensing (IRS) satellites to capture medium-resolution Earth observation data for applications like agriculture and land-use mapping.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.