BeagleBone Black
E762589
BeagleBone Black is a low-cost, community-supported single-board computer based on an ARM Cortex-A8 processor, commonly used for embedded systems, robotics, and hardware prototyping.
All labels observed (1)
| Label | Occurrences |
|---|---|
| BeagleBone Black canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T8856190 — 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: BeagleBone Black Context triple: [ev3dev, targetHardware, BeagleBone Black]
-
A.
Raspberry Pi
Raspberry Pi is a low-cost, credit card–sized single-board computer widely used for education, DIY electronics projects, and lightweight computing tasks.
-
B.
Raspberry Pi Pico
Raspberry Pi Pico is a low-cost, microcontroller-based development board from the Raspberry Pi Foundation built around the RP2040 chip for embedded and hobbyist projects.
-
C.
Calliope mini
Calliope mini is a small educational microcontroller board designed to teach children and beginners programming and electronics through interactive projects.
-
D.
Nvidia Tegra X1
The Nvidia Tegra X1 is a mobile system-on-chip that combines ARM CPU cores with an integrated Maxwell-based GPU, widely known for powering devices like the Nintendo Switch.
-
E.
NVIDIA Jetson embedded modules
NVIDIA Jetson embedded modules are compact, power-efficient computing platforms designed for edge AI and robotics applications, integrating GPU-accelerated processing for tasks like computer vision and deep learning.
- 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: BeagleBone Black Target entity description: BeagleBone Black is a low-cost, community-supported single-board computer based on an ARM Cortex-A8 processor, commonly used for embedded systems, robotics, and hardware prototyping.
-
A.
Raspberry Pi
Raspberry Pi is a low-cost, credit card–sized single-board computer widely used for education, DIY electronics projects, and lightweight computing tasks.
-
B.
Raspberry Pi Pico
Raspberry Pi Pico is a low-cost, microcontroller-based development board from the Raspberry Pi Foundation built around the RP2040 chip for embedded and hobbyist projects.
-
C.
Calliope mini
Calliope mini is a small educational microcontroller board designed to teach children and beginners programming and electronics through interactive projects.
-
D.
Nvidia Tegra X1
The Nvidia Tegra X1 is a mobile system-on-chip that combines ARM CPU cores with an integrated Maxwell-based GPU, widely known for powering devices like the Nintendo Switch.
-
E.
NVIDIA Jetson embedded modules
NVIDIA Jetson embedded modules are compact, power-efficient computing platforms designed for edge AI and robotics applications, integrating GPU-accelerated processing for tasks like computer vision and deep learning.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
open hardware platform
ⓘ
single-board computer ⓘ |
| architecture | ARM NERFINISHED ⓘ |
| bootSource |
microSD card
ⓘ
on-board eMMC ⓘ |
| capeDescription | Supports plug-in expansion boards called capes ⓘ |
| communitySupported | true ⓘ |
| cpu | Texas Instruments Sitara AM335x NERFINISHED ⓘ |
| cpuClockSpeed | 1 GHz ⓘ |
| cpuCore | ARM Cortex-A8 NERFINISHED ⓘ |
| debugInterface | JTAG (via header) ⓘ |
| developer | BeagleBoard.org Foundation NERFINISHED ⓘ |
| ethernetPort | 10/100 Mbps RJ45 ⓘ |
| formFactor | credit-card-sized board ⓘ |
| gpioPinCount | 92 ⓘ |
| gpioPins | 2×46-pin headers ⓘ |
| hasCapeInterface | true ⓘ |
| hasOnboardLEDs | true ⓘ |
| hasPRU | true ⓘ |
| intendedUse |
education
ⓘ
embedded systems ⓘ hardware prototyping ⓘ robotics ⓘ |
| license | open hardware design files ⓘ |
| manufacturer | CircuitCo NERFINISHED ⓘ |
| osSupport |
Android (community ports)
ⓘ
Debian GNU/Linux NERFINISHED ⓘ Ubuntu NERFINISHED ⓘ other Linux distributions ⓘ Ångström Linux NERFINISHED ⓘ |
| powerInput |
5V DC barrel jack
ⓘ
USB NERFINISHED ⓘ |
| predecessor | BeagleBone NERFINISHED ⓘ |
| pruDescription | Two 32-bit Programmable Real-time Units for real-time control ⓘ |
| ram | 512 MB DDR3 ⓘ |
| releaseYear | 2013 ⓘ |
| storage | 4 GB eMMC flash ⓘ |
| storageExpansion | microSD card slot ⓘ |
| supportsBoneScript | true GENERATED ⓘ |
| supportsCloud9IDE | true GENERATED ⓘ |
| supportsI2C | true GENERATED ⓘ |
| supportsPWM | true ⓘ |
| supportsSPI | true GENERATED ⓘ |
| supportsUART | true GENERATED ⓘ |
| usbPort |
USB 2.0 host
ⓘ
USB client ⓘ |
| videoOutput | micro HDMI ⓘ |
| wordSize | 32-bit ⓘ |
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: BeagleBone Black Description of subject: BeagleBone Black is a low-cost, community-supported single-board computer based on an ARM Cortex-A8 processor, commonly used for embedded systems, robotics, and hardware prototyping.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.