pos tag 0.00324763
pos tags 0.0029949
previous word 0.0026151010000000003
word context 0.002606382
pos tagging 0.002576777
current word 0.002541176
pos tagger 0.002537496
tagging model 0.002504527
different pos 0.002503623
unknown word 0.0024505
standard pos 0.002441809
same pos 0.002433878
word accord 0.0024254180000000004
head word 0.0024166160000000003
ous word 0.002392403
vious word 0.002387696
snow model 0.002383835
new model 0.002360946
trigram model 0.002352133
traditional pos 0.002243254
contextual model 0.002239844
ing model 0.002214379
entropy model 0.002205291
markov model 0.002188526
brill pos 0.002185113
case model 0.002155508
sign pos 0.002145641
sequential model 0.002099979
memm model 0.002099312
model acc 0.0020904599999999997
gram model 0.002086975
mixed model 0.002083017
quential model 0.002076935
tag set 0.001961164
model 0.0018291
sparse tag 0.001701013
test data 0.001678868
input features 0.001643261
training data 0.0016384429999999998
iob tag 0.001610165
data set 0.001570555
syntactic information 0.00155054
basic features 0.0015495889999999999
feature set 0.001523576
learning algorithm 0.001509973
standard data 0.00149613
new data 0.0014875169999999998
sic features 0.001475381
suffix features 0.001474523
other approach 0.001454655
data problem 0.0014518579999999999
complex information 0.0014050690000000001
few words 0.001398226
certain words 0.001382558
close tags 0.001376846
other models 0.001374966
local information 0.001355211
head words 0.001354666
syntactical information 0.001347805
tactic information 0.001343481
rare words 0.0013324600000000002
tical information 0.001314586
sparse data 0.0013104039999999998
new algorithm 0.001255413
voting algorithm 0.001238479
basic feature 0.001233531
train data 0.001225857
features 0.00122475
distinct feature 0.001212962
feature sets 0.001211773
flexible feature 0.0011938320000000001
rich feature 0.001187413
trigram models 0.001176004
parse tree 0.001162204
set size 0.001159765
second approach 0.001149532
learning algorithms 0.001144194
learning architecture 0.001134703
learning bias 0.001123427
supertagging algorithm 0.0011156360000000001
machine learning 0.0011145830000000002
learning techniques 0.001105814
elementary tree 0.001104728
good results 0.001101246
learning tool 0.001090995
words 0.00107948
probability estimation 0.001079027
ementary tree 0.0010737009999999998
information 0.00106835
other machine 0.001050172
inference algorithm 0.001043501
chine learning 0.001040438
other hand 0.001004923
distribution function 9.9629E-4
approach conflicts 9.79372E-4
other transitions 9.75715E-4
viterbi algorithm 9.714840000000001E-4
other scans 9.684159999999999E-4
large size 9.661100000000001E-4
sirable results 9.47936E-4
