word context 0.001955188
word features 0.0018263849999999998
test data 0.001790135
similar word 0.0017799589999999998
training data 0.0017672259999999998
word sense 0.001766141
previous word 0.001742034
attachment accuracy 0.001728059
word class 0.001722702
data set 0.001720062
attachment algorithm 0.00166144
possible attachment 0.0016226069999999999
word approximations 0.0015574299999999998
phrase attachment 0.001553165
attachment decision 0.001531647
attachment disambiguation 0.001528813
word newspaper 0.0015252879999999999
word approximation 0.0015236809999999998
prepositional attachment 0.00146349
unambiguous data 0.001449283
journal data 0.0014372249999999999
average attachment 0.001436072
final attachment 0.0014230509999999998
alternative attachment 0.001419947
attachment score 0.001414897
data extraction 0.001413933
data the 0.001413754
ambiguous data 0.00141252
data flow 0.001398561
attachment ambiguity 0.001393907
attachment scores 0.0013933819999999999
data sets 0.001386912
common attachment 0.00138433
adjectival attachment 0.001383202
attachment decisions 0.001378713
rbial attachment 0.00137302
attachment sites 0.001364335
sparse data 0.0013628849999999999
attachment site 0.001358244
target attachment 0.001357671
adverbial attachment 0.001357158
attachment approximation 0.0013395409999999999
same test 0.0013357450000000002
attachment birthday 0.0013355519999999998
learning accuracy 0.001273106
supervised learning 0.0012587520000000001
test set 0.0012542170000000002
classification model 0.0012289929999999998
other noun 0.00117013
same source 0.001168151
lexical information 0.001166273
supervised algorithm 0.001165465
words algorithm 0.001149698
training examples 0.001132379
same dependency 0.001128527
words table 0.0011179240000000002
entropy model 0.001117641
attachment 0.00110484
feature space 0.001094942
such examples 0.0010892179999999999
similar words 0.0010840770000000001
system accuracy 0.001079989
first sentence 0.001065413
model roth 0.001064386
supervised approach 0.001057401
full context 0.001023735
method learning 0.001022392
large corpus 0.001014597
frequency table 0.001003549
context salad 0.001002768
human accuracy 0.001001158
supervised methods 9.968099999999999E-4
testing corpus 9.87626E-4
disambiguation algorithm 9.80573E-4
noun phrase 9.743849999999999E-4
similar performance 9.71207E-4
class features 9.71127E-4
other approaches 9.58833E-4
the test 9.47909E-4
supervised algorithms 9.42345E-4
language disambiguation 9.39003E-4
mutual information 9.3837E-4
words collocation 9.345670000000001E-4
parsed corpus 9.295740000000001E-4
previous sentence 9.20595E-4
correct incorrect 9.16547E-4
unsupervised methods 9.12202E-4
example sentence 9.09227E-4
discourse context 9.060419999999999E-4
newspaper corpus 9.05693E-4
accuracy clbase 9.05203E-4
labelled corpus 9.03219E-4
sense disambiguation 9.01134E-4
context contextually 9.010499999999999E-4
nonsensical context 8.997569999999999E-4
unsupervised method 8.96762E-4
several language 8.92768E-4
dependency tree 8.78298E-4
accuracy reconstructed 8.649010000000001E-4
reported accuracy 8.626930000000001E-4
