word class 0.003700956
target word 0.003516601
word classes 0.00350621
word sense 0.003499684
word apple 0.0034837429999999996
word news 0.003483365
annotated word 0.0034516079999999997
previous word 0.0034081019999999997
hierarchical word 0.003405273
source word 0.0033929069999999997
head word 0.003352081
word battle 0.003327181
word pomegranate 0.003313287
word ontologies 0.003312107
word taxon 0.003311106
other words 0.003046194
clustering words 0.002923031
fruit words 0.002580307
vocabulary words 0.002559171
tween words 0.002518301
rare words 0.002518092
dependent words 0.002516045
pendent words 0.002504209
morphological features 0.002259022
words 0.00225851
baseline model 0.00224009
tagging model 0.002187538
model accuracy 0.0020789709999999998
model our 0.001996239
entropy model 0.001986836
model con 0.001958996
combined model 0.001958066
ging model 0.00195204
ing features 0.001886897
dependencies features 0.001846515
feature set 0.001840278
local features 0.001815763
taxonomical features 0.001735405
distinct features 0.001730077
posn features 0.001715022
model 0.00169842
pos tag 0.001690649
ing feature 0.001557037
feature sets 0.001536699
training data 0.001535107
tag set 0.001484361
tag information 0.001473432
features 0.00146853
important feature 0.001468226
single feature 0.001458337
feature functions 0.00143064
useful feature 0.001412895
feature selection 0.00140839
pos tagging 0.001397014
cate feature 0.0013927030000000001
feature predicates 0.001390488
dency feature 0.001385292
pos tagger 0.0013580740000000001
experimental data 0.001346381
semantic context 0.001340655
much data 0.001332359
large corpus 0.001332077
test corpus 0.0013057099999999999
training corpus 0.001289999
semantic class 0.001283093
bilingual data 0.001268859
semantic tags 0.0012680579999999999
main tag 0.001248361
same information 0.001233933
test set 0.001229426
syntactic information 0.001225339
correct tag 0.0012062219999999998
semantic categories 0.001196487
entropy pos 0.0011963120000000002
syntactic tags 0.001154891
pos syntax 0.001153282
labeling text 0.001142808
feature 0.00113867
models 0.00111107
language processing 0.00110168
unannotated text 0.001096634
tated text 0.001091472
ning text 0.001091472
natural language 0.001088065
semantic sense 0.001081821
corpus vocabulary 0.0010785529999999999
language communication 0.001074529
simple set 0.001065774
full set 0.001063074
cluster set 0.001057602
clustering method 0.00104488
spoken language 0.0010430370000000001
ambiguous tag 0.0010413179999999998
primary corpus 0.001041273
local context 0.0010400610000000001
semantic label 0.00101472
much information 0.001000038
tagging errors 9.84359E-4
clustering process 9.83364E-4
mutual information 9.76087E-4
