word sense 0.00460426
sense data 0.00386056
sense information 0.003630332
wordnet sense 0.0035813959999999997
sense disambiguation 0.003462762
first sense 0.0032277369999999996
automatic sense 0.0031448279999999997
correct sense 0.003131293
tool sense 0.0031133109999999997
semantic information 0.0031082619999999997
sense ranking 0.003072962
ﬁrst sense 0.003037827
sense infor 0.003037363
sense informa 0.0030334949999999998
animal sense 0.003033045
frequent sense 0.0030316009999999997
sense annotations 0.0030272949999999997
sense predictions 0.0030176079999999997
quent sense 0.003015057
semantic features 0.002974277
semantic disambiguation 0.002940692
semantic class 0.002822116
sense 0.00275022
semantic representation 0.00274957
semantic category 0.0026618659999999997
different word 0.002654447
semantic classes 0.002649763
semantic categories 0.002609093
semantic tags 0.0025888309999999998
semantic representations 0.0025546659999999997
semantic disam 0.002541922
semantic represen 0.002521589
semantic resource 0.002517318
semantic granularity 0.002515057
semantic dis 0.002513716
semantic options 0.0025111459999999997
semantic fea 0.00249988
semantic rep 0.002495467
semantic generalisation 0.002494897
semantic codes 0.002494897
semantic spe 0.002493091
semantic repre 0.002493091
semantic ﬁle 0.002493091
target word 0.002194141
rate word 0.002154121
unsupervised word 0.002148591
word forms 0.002134805
word crane 0.002121535
other words 0.0018532800000000001
lexical features 0.001789137
test data 0.001703783
parse model 0.001653472
training data 0.001607071
standard data 0.00154341
syntactic disambiguation 0.001543256
parsing model 0.001539735
original words 0.001509603
polysemous words 0.0014895989999999999
nal words 0.0014750709999999999
merging words 0.001471575
different senses 0.001462667
basic model 0.001437313
rrr data 0.001423919
tion model 0.0014167160000000002
syntactic parse 0.001407656
same attachment 0.001404144
ptb data 0.0013944320000000001
lexical database 0.0013887460000000002
selection model 0.001383004
different parsers 0.001362361
lexical head 0.001360567
lexical phrases 0.001357484
lexical semantics 0.001355505
bilexical model 0.001353636
biguation model 0.00134699
similarity measures 0.0013439839999999999
lexical seman 0.001340042
attachment performance 0.001336672
treebank parser 0.001332718
parser set 0.00133146
wsd method 0.001313992
parser performance 0.001307637
parse disambiguation 0.001289484
automatic wsd 0.001287693
different approaches 0.00126553
same dataset 0.001260875
extraction system 0.001250731
attachment methods 0.001233019
test set 0.001210656
possible attachment 0.001208486
mantic information 0.001207891
words 0.00120499
disambiguation methods 0.001202279
wsd strategy 0.001200609
attachment task 0.001194884
synset wsd 0.001188647
parsing models 0.001183498
treebank parsers 0.0011804250000000001
unsupervised system 0.001177668
joint wsd 0.001171514
