model accuracy 0.002934415
model dictionary 0.0028898559999999997
hmm model 0.0025669309999999997
simple model 0.0025403409999999998
emission model 0.0025269439999999997
wiktionary model 0.0025265229999999997
markov model 0.0025038269999999997
pervised model 0.00249425
sparse model 0.002486251
multinomial model 0.002483169
projection model 0.0024616
different word 0.002458246
word pos 0.002455276
model param 0.002450763
model parameters 0.002446552
der model 0.0024435629999999997
pos tag 0.002282816
language word 0.002208774
model 0.00220158
tag dictionary 0.002101126
tag set 0.0020613940000000002
word type 0.002060457
word tokens 0.002056209
ing word 0.002009496
word types 0.001960283
word form 0.001956243
particular word 0.0019416899999999998
correct tag 0.001904701
word alignments 0.0018905719999999999
tag disambiguation 0.001883685
frequent word 0.001856491
word count 0.001850825
word shape 0.0018356989999999999
tag sequence 0.001831699
word contexts 0.001826776
word counts 0.001825543
word identity 0.0018245099999999999
word align 0.0018245099999999999
tag errors 0.001761741
tag sets 0.001752738
level tag 0.001745763
wiktionary tag 0.001737793
prior tag 0.001714076
pos tags 0.001709137
bank tag 0.001702249
universal tag 0.001695187
tag dictionaries 0.001672448
tag num 0.0016605909999999999
pos tagging 0.0015954979999999999
corpus tags 0.001566532
several words 0.001543074
different models 0.001523552
possible pos 0.001495446
training text 0.0014933540000000001
possible tags 0.001464651
tagging accuracy 0.001458367
several tags 0.001454365
unknown words 0.0014459809999999998
many words 0.001382284
different languages 0.0013309440000000001
pos taggers 0.001293345
several models 0.00126581
unsupervised pos 0.001264761
common words 0.001264164
specific information 0.001245572
information clustering 0.001234409
additional information 0.001215416
pos definition 0.001205916
able words 0.001200421
frequent words 0.001199061
english text 0.001197109
text methods 0.001190435
covered words 0.001181619
average accuracy 0.0011798870000000001
mutual information 0.0011772599999999999
det tags 0.001173366
different line 0.001171475
group words 0.0011714359999999999
dictionary coverage 0.001170905
bank information 0.001167321
different ways 0.001163943
additional data 0.00115848
different sections 0.001156731
such models 0.001156675
universal pos 0.001152303
different setup 0.0011509900000000002
pos induction 0.001146004
start tags 0.001141232
parallel data 0.001139442
annotated data 0.001134764
information retrieval 0.001125591
bilingual data 0.001125517
information extraction 0.001122865
training sentences 0.001122594
different domains 0.001122488
universal tags 0.001121508
little information 0.001120097
different lan 0.0011186920000000001
different versions 0.0011175030000000002
true tags 0.001117238
