---

input (aspect of gate) → HasProperty → high	0.84
input (aspect of neural network) → ReceivesAction → weighted	0.84
input (aspect of gate) → HasProperty → low	0.75
input (aspect of neural network) → ReceivesAction → normalized	0.74
input (aspect of amplifier) → HasProperty → active	0.70
input (aspect of gate) → HasProperty → true	0.68
input (aspect of amplifier) → HasA → output	0.68
input (aspect of latch) → HasProperty → high	0.68
input (aspect of multiplexer) → HasProperty → high	0.68
visual cue (subgroup of cue) → IsA → input	0.68
electrical signal (subgroup of signal) → IsA → input	0.68
pwm signal (subgroup of signal) → IsA → input	0.68
amplifier → HasA → input	0.68
input (aspect of latch) → CapableOf → latch 10	0.63
coach → HasA → input	0.63
parent → HasA → input	0.62
input (aspect of gate) → HasProperty → false	0.61
process → HasA → input	0.60
input (aspect of multiplexer) → CapableOf → receive signal	0.60
input (aspect of latch) → HasProperty → low	0.59
parent (aspect of child) → HasA → input	0.59
multiplexer → HasA → input	0.59
node → HasA → input	0.58
input (aspect of neural network) → ReceivesAction → received	0.58
input (aspect of gate) → HasProperty → zero	0.58
input (aspect of gate) → ReceivesAction → raised to high logic level	0.58
input (aspect of multiplexer) → ReceivesAction → connected to output	0.57
input (aspect of gate) → HasProperty → equal	0.56
digital signal (subgroup of signal) → IsA → input	0.56
input (aspect of gate) → HasProperty → positive	0.55
tv → HasA → input	0.54
student (aspect of teacher) → HasA → input	0.54
input (aspect of multiplexer) → ReceivesAction → selected	0.54
member (aspect of club) → HasA → input	0.53
interface → HasA → input	0.52
input (aspect of neural network) → HasA → weight	0.52
input (aspect of neural network) → ReceivesAction → sampled	0.52
resident → HasA → input	0.52
function → HasA → input	0.52
input (aspect of amplifier) → ReceivesAction → coupled to output	0.51
input (aspect of amplifier) → ReceivesAction → connected to the output	0.51
audio signal (subgroup of signal) → IsA → input	0.50
character → HasProperty → input	0.50
input (aspect of amplifier) → HasProperty → high	0.48
input (aspect of amplifier) → ReceivesAction → connected to first and second output terminals	0.48
input (aspect of amplifier) → CapableOf → receive same analog input signal	0.45
input (aspect of amplifier) → ReceivesAction → coupled with second signal path	0.45
input (aspect of neural network) → ReceivesAction → multiplied by weight	0.45
command → HasPrerequisite → input	0.43
analog signal (subgroup of signal) → IsA → input	0.43
input (aspect of latch) → ReceivesAction → shown in fig	0.42
input (aspect of latch) → ReceivesAction → connected	0.42
subwoofer → HasA → input	0.42
input (aspect of amplifier) → ReceivesAction → supplied with an input voltage	0.42
input (aspect of amplifier) → ReceivesAction → configured to receive an input signal	0.42
splitter → HasA → input	0.42
input (aspect of multiplexer) → HasProperty → true	0.41
input (aspect of amplifier) → ReceivesAction → sampled	0.41
input (aspect of gate) → ReceivesAction → forced to low logic level	0.41
input (aspect of gate) → ReceivesAction → processed	0.41
input (aspect of gate) → ReceivesAction → driven	0.41
input (aspect of multiplexer) → ReceivesAction → enabled	0.41
member (aspect of church) → HasA → input	0.41
output → SimilarTo → the input	0.40
input (aspect of multiplexer) → ReceivesAction → connected to the output of nand gate	0.40
original image (subgroup of image) → IsA → input	0.40
board (aspect of fund) → HasA → input	0.40
input (aspect of latch) → HasProperty → equal	0.38
input (aspect of amplifier) → HasProperty → positive	0.37
input (aspect of amplifier) → ReceivesAction → amplified	0.37
input (aspect of amplifier) → ReceivesAction → connected by conductor	0.37
input (aspect of gate) → HasProperty → active	0.37
circuit → HasA → input	0.36
input (aspect of neural network) → CapableOf → produce output	0.36
output → RelatedTo → the input	0.36
input (aspect of gate) → HasProperty → inverted	0.34
member (aspect of party) → HasA → input	0.34
input (aspect of multiplexer) → HasProperty → low	0.33
input (aspect of multiplexer) → HasProperty → active	0.33
input (aspect of multiplexer) → ReceivesAction → coupled to the output of alu	0.33
input (aspect of multiplexer) → ReceivesAction → tied to ground	0.33
input (aspect of multiplexer) → ReceivesAction → gated	0.33
input (aspect of multiplexer) → ReceivesAction → provided to the data processor	0.33
field → HasPrerequisite → input	0.33
input (aspect of latch) → HasProperty → active	0.32
input (aspect of gate) → ReceivesAction → added	0.32
input (aspect of gate) → ReceivesAction → connected	0.32
input (aspect of amplifier) → CapableOf → receive the acceleration signal	0.32
input (aspect of amplifier) → ReceivesAction → grounded	0.32
input (aspect of amplifier) → ReceivesAction → coupled to anode ends of the series	0.32
input (aspect of amplifier) → ReceivesAction → connected	0.32
input (aspect of amplifier) → ReceivesAction → provided	0.32
input (aspect of amplifier) → ReceivesAction → tied to ground	0.32
input (aspect of amplifier) → ReceivesAction → coupled to the lna	0.32
default → SimilarTo → input	0.31
script → HasPrerequisite → input	0.30
resident (aspect of city) → HasA → input	0.29
input (aspect of gate) → HasProperty → negative	0.29
input (aspect of gate) → ReceivesAction → changed	0.29
input (aspect of gate) → ReceivesAction → connected to the output of an or	0.29
input (aspect of gate) → ReceivesAction → gated	0.29
input (aspect of neural network) → ReceivesAction → determined to be unreliable	0.27
input (aspect of amplifier) → CapableOf → present high impedance	0.25
input (aspect of neural network) → CapableOf → represent query	0.25
input (aspect of neural network) → CapableOf → apply the high-capacity sub	0.25
input (aspect of amplifier) → HasA → priority	0.25
input (aspect of amplifier) → HasProperty → negative	0.25
input (aspect of flop) → HasProperty → high	0.25
input (aspect of latch) → HasProperty → positive	0.25
input (aspect of multiplexer) → HasProperty → zero	0.25
input (aspect of neural network) → HasProperty → zero	0.25
input (aspect of neural network) → HasProperty → positive	0.25
input (aspect of amplifier) → ReceivesAction → balanced	0.25
input (aspect of amplifier) → ReceivesAction → coupled to the input node	0.25
input (aspect of amplifier) → ReceivesAction → set	0.25
input (aspect of amplifier) → ReceivesAction → renamed	0.25
input (aspect of amplifier) → ReceivesAction → fed to the amplifier stage	0.25
input (aspect of amplifier) → ReceivesAction → driven beyond supply	0.25
input (aspect of amplifier) → ReceivesAction → connected via resistor	0.25
input (aspect of amplifier) → ReceivesAction → switched	0.25
input (aspect of amplifier) → ReceivesAction → associated with a plurality of outputs	0.25
input (aspect of gate) → ReceivesAction → fed	0.25
input (aspect of gate) → ReceivesAction → grounded	0.25
input (aspect of gate) → ReceivesAction → set	0.25
input (aspect of gate) → ReceivesAction → connected to other circuit elements	0.25
input (aspect of latch) → ReceivesAction → coupled to first node	0.25
input (aspect of latch) → ReceivesAction → provided	0.25
input (aspect of latch) → ReceivesAction → coupled to the input circuit output node	0.25
input (aspect of latch) → ReceivesAction → connected to the output of the inverter	0.25
input (aspect of multiplexer) → ReceivesAction → coupled to first node	0.25
input (aspect of multiplexer) → ReceivesAction → connected	0.25
input (aspect of multiplexer) → ReceivesAction → set to a logic one 1level	0.25
input (aspect of multiplexer) → ReceivesAction → set to output	0.25
input (aspect of multiplexer) → ReceivesAction → coupled to a carry output	0.25
input (aspect of multiplexer) → ReceivesAction → shown in fig	0.25
input (aspect of neural network) → ReceivesAction → multiplied by the weights of the connections	0.25
input (aspect of neural network) → ReceivesAction → transmitted to remote processing system	0.25
input (aspect of latch) → RelatedTo → request	0.25
agriculture → HasPrerequisite → input	0.25
bellwether → HasA → input	0.25
generator → HasA → input	0.25
invitation → HasA → input	0.25
receiver → HasA → input	0.25
subordinate → HasA → input	0.25
right (aspect of citizen) → HasA → input	0.25
output (aspect of function) → SimilarTo → the input	0.25
right (aspect of parent) → HasA → input	0.21
input (aspect of gate) → CreatedBy → the project team	0.20
input (aspect of neural network) → HasProperty → negative	0.16
input (aspect of gate) → ReceivesAction → selected	0.09
value (aspect of expression) → HasProperty → input	0.09