tag words 0.0031201700000000002
hmm model 0.0026809650000000004
pos tag 0.00264939
context model 0.0026195130000000004
bayesian model 0.0025799390000000003
class model 0.0025087860000000003
common model 0.0024261480000000004
markov model 0.0024015200000000003
effective model 0.002355326
paradigmatic model 0.002344754
unknown word 0.002284057
similar word 0.002247551
word suffix 0.002184118
unknown words 0.002158507
similar words 0.002122001
model 0.00208322
tag set 0.0020692970000000003
word types 0.002022669
word classes 0.001992394
words algorithm 0.001971339
word stem 0.001963485
class words 0.0019578959999999998
word segmentation 0.001955108
known word 0.001942096
stochastic tag 0.001938508
word distribu 0.0019351210000000002
word triplets 0.001912713
several words 0.001910733
tag distri 0.0018909220000000002
mapping words 0.001874859
tag trigram 0.0018741300000000001
tag selection 0.0018646130000000002
pos tagging 0.0018637200000000001
likely tag 0.0018586470000000002
probable tag 0.001854778
valid tag 0.0018446970000000002
tag ngrams 0.001842642
same data 0.001842625
known words 0.001816546
frequent words 0.0018120809999999999
tween words 0.0018050969999999999
oov words 0.001790402
stop words 0.001787585
neighboring words 0.001787585
neighbouring words 0.001787585
training data 0.001741699
possible pos 0.001738636
text data 0.0017170409999999999
training corpus 0.001697329
english pos 0.001662261
pos accuracy 0.0016292250000000002
wsj data 0.001589163
test corpus 0.001549619
wsj corpus 0.001544793
words 0.00153233
pos uniform 0.0015319090000000001
pos tagger 0.001528905
other models 0.001487166
context features 0.001475525
unsupervised pos 0.001456714
possible tags 0.00145367
corpus frequency 0.0014423180000000002
corpus counts 0.0014414970000000001
labeled data 0.0014383080000000001
data sets 0.001437887
unlabeled data 0.001430176
such models 0.001422599
pos tagset 0.0013918440000000002
pos prt 0.001378054
other results 0.00137495
complete pos 0.001372932
tagging accuracy 0.0013698450000000002
pos informa 0.001362506
same method 0.001356248
annotated corpus 0.001347677
hmm models 0.001346322
learning method 0.001340047
similar models 0.0013382480000000002
probable pos 0.001328488
raw corpus 0.001327189
hmm learning 0.0013268989999999999
sible pos 0.001318762
extended pos 0.001316036
untagged corpus 0.0013083650000000001
morphological context 0.001283647
standard distribution 0.001275901
same feature 0.0012745249999999999
tokens training 0.001267182
initial values 0.0012649150000000001
state features 0.001263738
other values 0.001259224
unknown tokens 0.00124893
hmm training 0.001242174
spelling features 0.001233718
tagging task 0.00123209
surface features 0.001212324
morphological disambiguation 0.0012082479999999999
uniform distribution 0.001207195
tagging methods 0.001207086
hebrew morphological 0.001205524
