semantic role 0.00295409
syntactic tree 0.0026974800000000004
semantic argument 0.0025588169999999997
syntactic features 0.00245328
parse tree 0.00241184
syntactic parser 0.002242808
semantic roles 0.002188786
semantic tags 0.002163127
semantic parsing 0.002125336
semantic tag 0.002116856
semantic constituent 0.0020851719999999997
tree information 0.0020781840000000003
semantic extraction 0.002045303
semantic labels 0.002031519
shallow semantic 0.001941115
semantic understanding 0.0019242769999999998
semantic classifi 0.001921831
syntactic analysis 0.001847611
syntactic path 0.001814195
word position 0.0017920889999999997
other features 0.001777957
role label 0.001741789
same features 0.001735356
role labeling 0.001728966
role tagging 0.001714012
syntactic labels 0.001707269
syntactic parsers 0.001691795
semantic 0.00168685
word sense 0.00164523
syntactic constituents 0.001638253
head word 0.001637519
tree component 0.001627767
syntactic structures 0.001626751
role labels 0.001611909
word representation 0.001607461
tree struc 0.001605964
new feature 0.001579385
important role 0.001574108
word vectors 0.001573098
tree computation 0.0015707820000000002
original word 0.001567172
parse trees 0.0015498110000000001
learning system 0.001534168
ith word 0.0015230749999999998
feeding word 0.0015204709999999998
word indices 0.001517495
propbank features 0.0015108189999999998
feature vectors 0.0014734280000000002
feature types 0.0014677700000000002
full parse 0.001436832
initial feature 0.0014342180000000001
ing system 0.00142126
different approach 0.0014137
training set 0.001401081
argument classification 0.001392332
many words 0.001386559
annotated parse 0.0013708750000000001
final model 0.001353477
argument structure 0.001340899
predicate argument 0.001339642
statistical model 0.001337813
features currently 0.001326985
different network 0.001325981
assert system 0.001263369
training data 0.0012560940000000001
guage model 0.001251206
classification task 0.0012272989999999998
different premise 0.001211826
different spaces 0.001211826
test set 0.001192106
whole system 0.0011871849999999999
feature 0.00118113
numbering system 0.001175908
tactic parser 0.00115656
such data 0.001154157
constituent information 0.001141626
first layer 0.001139977
shallow parser 0.001134473
same accuracy 0.0011341659999999998
features 0.00109068
classification performance 0.001089673
other methods 0.001084582
training examples 0.001083831
parse 0.00107696
training process 0.00107328
infrequent words 0.001073222
language models 0.001064036
temporal information 0.001047956
labeled training 0.00103717
segment information 0.001035728
first line 0.0010185020000000001
same class 0.001013211
classification accuracy 0.001009855
same type 0.001009526
model 0.00100734
complete set 0.001005244
first svm 0.001004922
such applications 0.001000861
learning approaches 9.9293E-4
test accuracy 9.88353E-4
