Long Term Evolution for Machines
E523052
Long Term Evolution for Machines is a low-power wide-area cellular technology based on LTE, designed to provide efficient, secure, and cost-effective connectivity for Internet of Things (IoT) devices.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Long Term Evolution for Machines canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T5480154 — 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: Long Term Evolution for Machines Context triple: [LTE-M, standsFor, Long Term Evolution for Machines]
-
A.
LTE-Advanced
LTE-Advanced is an enhanced 4G mobile communication standard that significantly improves data rates, capacity, and network efficiency over earlier LTE systems.
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B.
LTE-Advanced Pro
LTE-Advanced Pro is an enhanced 4G mobile broadband technology that bridges LTE-Advanced and 5G by offering higher data rates, improved capacity, and advanced features such as carrier aggregation and enhanced MIMO.
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C.
Access and Mobility Management Function
The Access and Mobility Management Function (AMF) is a key 5G core network control-plane function responsible for user equipment registration, connection and mobility management, and access authentication.
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D.
LTE
LTE (Long Term Evolution) is a high-speed wireless communication standard for mobile devices and data terminals, widely used as the foundation of 4G cellular networks.
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E.
3GPP RAN
3GPP RAN is the standards group within 3GPP responsible for specifying the radio access network technologies and protocols used in mobile communication systems such as LTE and 5G.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Long Term Evolution for Machines Target entity description: Long Term Evolution for Machines is a low-power wide-area cellular technology based on LTE, designed to provide efficient, secure, and cost-effective connectivity for Internet of Things (IoT) devices.
-
A.
LTE-Advanced
LTE-Advanced is an enhanced 4G mobile communication standard that significantly improves data rates, capacity, and network efficiency over earlier LTE systems.
-
B.
LTE-Advanced Pro
LTE-Advanced Pro is an enhanced 4G mobile broadband technology that bridges LTE-Advanced and 5G by offering higher data rates, improved capacity, and advanced features such as carrier aggregation and enhanced MIMO.
-
C.
Access and Mobility Management Function
The Access and Mobility Management Function (AMF) is a key 5G core network control-plane function responsible for user equipment registration, connection and mobility management, and access authentication.
-
D.
MIMO
MIMO (Multiple-Input Multiple-Output) is a wireless communication technique that uses multiple transmitting and receiving antennas to significantly increase data throughput and link reliability.
-
E.
LTE
LTE (Long Term Evolution) is a high-speed wireless communication standard for mobile devices and data terminals, widely used as the foundation of 4G cellular networks.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
cellular communication technology
ⓘ
low-power wide-area network technology ⓘ |
| abbreviation | LTE-M NERFINISHED ⓘ |
| alternativeName |
LTE Cat-M
NERFINISHED
ⓘ
LTE Cat-M1 NERFINISHED ⓘ |
| basedOn |
LTE
NERFINISHED
ⓘ
Long Term Evolution NERFINISHED ⓘ |
| belongsToFamily | LTE Advanced Pro features ⓘ |
| compatibleWith | existing LTE networks ⓘ |
| competesWith |
NB-IoT
NERFINISHED
ⓘ
Narrowband IoT NERFINISHED ⓘ |
| designedFor |
extended battery life
ⓘ
low device complexity ⓘ low-cost IoT devices ⓘ low-power operation ⓘ wide-area coverage ⓘ |
| developedBy |
3GPP
NERFINISHED
ⓘ
3rd Generation Partnership Project NERFINISHED ⓘ |
| ITUCategory | IMT-Advanced 4G technology ⓘ |
| optimizedFor |
deep coverage scenarios
ⓘ
indoor coverage ⓘ |
| partOf | 4G LTE ecosystem ⓘ |
| provides |
cost-effective connectivity
ⓘ
energy-efficient connectivity ⓘ secure connectivity ⓘ |
| regionOfDeployment |
Asia-Pacific
NERFINISHED
ⓘ
Europe NERFINISHED ⓘ North America NERFINISHED ⓘ |
| standardizedIn |
3GPP Release 13
NERFINISHED
ⓘ
3GPP Release 14 NERFINISHED ⓘ |
| supports |
Internet of Things devices
ⓘ
VoLTE for IoT devices ⓘ machine-to-machine communication ⓘ massive IoT deployments ⓘ |
| supportsDataRates | up to about 1 Mbps ⓘ |
| supportsExtendedDiscontinuousReception | true ⓘ |
| supportsHalfDuplexOperation | true ⓘ |
| supportsMobility | true ⓘ |
| supportsPowerSavingMode | true ⓘ |
| supportsVoice | true ⓘ |
| typicalUseCases |
asset tracking
ⓘ
industrial IoT monitoring ⓘ smart city applications ⓘ smart metering ⓘ wearables connectivity ⓘ |
| uses | licensed spectrum ⓘ |
| usesCoreNetwork | Evolved Packet Core 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: Long Term Evolution for Machines Description of subject: Long Term Evolution for Machines is a low-power wide-area cellular technology based on LTE, designed to provide efficient, secure, and cost-effective connectivity for Internet of Things (IoT) devices.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.