sense tag 0.002210476
previous sense 0.002041026
judges sense 0.0020340469999999998
sense tags 0.001912067
single sense 0.001865691
sense distinctions 0.001853612
sense tagging 0.0018480929999999999
ing sense 0.001821875
latent sense 0.0017674829999999998
ton sense 0.0017436959999999999
givenn sense 0.001719343
sense groupings 0.001719343
sense distinction 0.001719343
favorn sense 0.001719343
class model 0.001630785
model parameters 0.0015888809999999999
bayes model 0.001517557
sense 0.00149757
tag set 0.0013189410000000001
data sample 0.001279866
data the 0.0012555819999999999
the data 0.0012555819999999999
model 0.001248
human judges 0.001238441
word instances 0.001232078
results table 0.001203167
other senses 0.001177735
single tag 0.001081027
disambiguation task 0.00106584
initial tag 0.001031875
confusion matrix 0.001021785
other words 0.001019905
overall agreement 0.0010154489999999999
majority tag 0.001004657
noun senses 0.001003243
latent tag 9.82819E-4
tag correlation 9.70669E-4
section agreement 9.65105E-4
first judge 9.62424E-4
many classification 9.62038E-4
original tag 9.517130000000001E-4
chance agreement 9.37708E-4
tuning tag 9.34644E-4
such categories 9.32129E-4
sentence level 9.19128E-4
second judge 9.18489E-4
classification process 9.16168E-4
actual agreement 9.10473E-4
automatic classification 9.10359E-4
classification systems 9.004950000000001E-4
perfect agreement 8.98636E-4
such techniques 8.93259E-4
classification experiment 8.92065E-4
the classification 8.80526E-4
pruning senses 8.798230000000001E-4
contingency table 8.74752E-4
natural language 8.732480000000001E-4
multiple judges 8.704990000000001E-4
level distinctions 8.69414E-4
difference measures 8.593680000000001E-4
reliable set 8.546070000000001E-4
table format 8.39827E-4
tingency table 8.38292E-4
table alb 8.36846E-4
previous section 8.36297E-4
man judges 8.35279E-4
corpus infor 8.34572E-4
possible level 8.265799999999999E-4
particular judges 8.20023E-4
automated classification 8.144910000000001E-4
classification sys 8.083060000000001E-4
nal classification 8.052010000000001E-4
previous background 7.93037E-4
language processing 7.846160000000001E-4
marginal counts 7.80909E-4
individual words 7.76782E-4
strong similarity 7.74999E-4
previous stud 7.70015E-4
judges increases 7.62576E-4
perienced judges 7.58022E-4
judges all 7.58022E-4
judges inereases 7.58022E-4
significance level 7.54115E-4
removing judge 7.51689E-4
discourse level 7.38699E-4
level distinc 7.35775E-4
recent work 7.34342E-4
grant number 7.298910000000001E-4
figure removing 7.27701E-4
moneyn figure 7.254639999999999E-4
lexical distinctions 7.09264E-4
marginal distributions 7.04334E-4
matrix 7.01345E-4
individual tags 6.92928E-4
similar tables 6.89047E-4
only exception 6.84775E-4
latent tags 6.8441E-4
future work 6.73291E-4
agreement 6.72264E-4
total probability 6.7091E-4
