different data 0.002027953
dependency parser 0.001963375
language model 0.001815353
data set 0.0017551889999999999
different error 0.001739789
same data 0.001726087
dependency parsing 0.0016935779999999998
pos model 0.0016884730000000002
tree model 0.0016722780000000001
training data 0.0016444440000000001
same parsing 0.0016110970000000001
such information 0.001541337
dependency tree 0.001539082
other words 0.001510887
language error 0.0015018710000000001
training set 0.001483187
parsing accuracy 0.001477118
chunk parser 0.001471588
oracle parser 0.001464328
constraint dependency 0.001449064
baseline parser 0.0014288920000000002
input data 0.0014095800000000001
dependency grammar 0.001402444
different knowledge 0.001397377
probabilistic parser 0.001387923
wcdg parser 0.0013860690000000002
language models 0.001363987
subsequent parser 0.001353634
parser eval 0.001352111
different predictors 0.001342425
different kinds 0.0013423200000000001
pos accuracy 0.001338817
different types 0.0013231520000000002
different amounts 0.001321267
test set 0.00131741
attachment words 0.001312061
different ways 0.001298314
different contributions 0.0012945550000000002
different methodologies 0.001293321
same test 0.0012883080000000002
parsing system 0.001274927
detailed model 0.0012654240000000002
probabilistic model 0.0012584340000000001
syntactic parsing 0.00124869
parsing problem 0.001237013
dependency trees 0.001223163
same input 0.001219221
model treetag 0.0012062140000000002
chunk parsing 0.001201791
parsing experiments 0.001187442
data col 0.001184979
such con 0.001182845
pos tagger 0.001180579
data collections 0.0011805750000000001
pus data 0.0011805750000000001
same way 0.0011786680000000001
attachment accuracy 0.001166694
natural language 0.001160444
full dependency 0.001158863
many rules 0.001152779
decision tree 0.001143991
labelled dependency 0.001129718
dependency labels 0.0011253819999999999
pos tag 0.0011248130000000001
such cases 0.0011209850000000001
wcdg parsing 0.001116272
parser 0.00111303
other components 0.001112778
following words 0.001104311
dependency attachments 0.0011006359999999999
high accuracy 0.001100233
additional information 0.0010978350000000001
hybrid parsing 0.001096108
correct pos 0.00109578
projective dependency 0.001083479
able dependency 0.001081956
dependency edges 0.00108187
other predictor 0.001080257
ambiguous words 0.0010775630000000001
standard pos 0.0010717
same regent 0.0010686720000000001
handwritten language 0.001068173
language definition 0.001067272
parsing ger 0.001065919
tive language 0.001063843
language expert 0.001058863
ural language 0.001056469
pos tags 0.001050349
such informa 0.001049698
average accuracy 0.0010493310000000001
ferent information 0.0010461630000000001
base set 0.001042041
word form 0.0010339820000000001
available tree 0.001021709
tabu set 0.001021429
resolution set 0.001019399
pos disambiguation 0.001019206
erroneous information 0.001015216
biguous words 0.001014474
information fusion 0.001011452
