model pos 0.00380515
processing model 0.003310581
simple model 0.003175578
probabilistic model 0.0031397940000000004
state model 0.003134702
model training 0.003086904
model parameters 0.0030421170000000004
current model 0.0030324210000000004
statistical model 0.0029836420000000003
markov model 0.002950444
accurate model 0.0029225120000000004
network model 0.0029130960000000004
scientific model 0.0028920110000000003
tional model 0.0028660430000000004
powerful model 0.002854502
model stud 0.002851515
model 0.00260148
same word 0.002240716
word sequence 0.002219987
current word 0.002199651
word frequency 0.0021138479999999998
frequency word 0.0021138479999999998
ambiguous word 0.002112952
word string 0.002095438
word recognition 0.002074007
disambiguating word 0.002046033
word break 0.002029077
critical word 0.002022795
word strings 0.002019723
possible pos 0.001997872
other sentence 0.001996292
sentence processing 0.0019920809999999997
different pos 0.001843305
human sentence 0.001811113
probability distribution 0.001764848
probabilistic pos 0.001741984
sentence process 0.001725234
pos tagging 0.0016879
same pos 0.001675676
pos sequence 0.001654947
empirical sentence 0.001647333
control sentence 0.0016459019999999999
ambiguous sentence 0.001627222
pos tagger 0.001622219
statistical pos 0.0015858320000000001
other ambiguity 0.001569869
lexical information 0.001569105
man sentence 0.0015662369999999998
whole sentence 0.001562612
probability decrease 0.001558739
bigram pos 0.001550083
sentence com 0.001546752
log probability 0.001538712
trol sentence 0.00153277
lexical ambiguity 0.001529214
likely pos 0.001527869
final probability 0.001526484
probability comparison 0.001523652
average probability 0.0015210150000000001
probability transition 0.001500906
transition probability 0.001500906
ditional probability 0.001490931
probability drop 0.001486354
true probability 0.001475324
processing data 0.001474312
pos sequences 0.001473594
joint probability 0.001472028
frequent pos 0.001464877
probability com 0.001462762
unlikely pos 0.001453317
dispreferred pos 0.001453317
ning probability 0.0014522720000000001
probability compar 0.001449329
time data 0.001415937
structural information 0.0014084710000000001
structural ambiguity 0.0013685799999999999
control sentences 0.001359833
ing data 0.001350482
example sentences 0.0013479520000000001
ambiguous sentences 0.001341153
reading data 0.0013352849999999999
possible tag 0.0013284680000000002
category ambiguity 0.001326632
computational models 0.0013253470000000002
sentence 0.00128298
path sentences 0.001263119
ous sentences 0.001260669
unambiguous sentences 0.001255538
biguous sentences 0.001251261
relative ambiguity 0.001250059
frequency information 0.001241586
later words 0.001241082
same data 0.001237217
ing time 0.001235997
reading time 0.0012208
disambiguating words 0.0012105459999999998
different reading 0.001209709
probability 0.00119899
distinct words 0.00118992
semantic information 0.001181929
