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model tags 0.0023859420000000003
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tag bigrams 0.002330966
hmm tag 0.002297441
tag transition 0.002286819
tag bigram 0.002278163
tag path 0.002273807
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only tag 0.002245241
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tag dictionary 0.002231828
tag dictionaries 0.002220949
likely tag 0.0022206500000000002
model tagging 0.002208443
viterbi tag 0.002202095
model performance 0.002189574
tag assignments 0.002174689
plete tag 0.002174082
tag transitions 0.002169744
tag frequencies 0.002157916
model minimization 0.002105468
small model 0.002045271
hmm model 0.002044721
emission model 0.0020265590000000003
model size 0.001986247
markov model 0.001973648
trained model 0.001938192
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supervised model 0.0019307590000000002
grammar set 0.0019229870000000001
training data 0.0018116500000000002
data set 0.001809187
full grammar 0.001796255
same data 0.001776636
test data 0.0017412740000000001
test word 0.001698354
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structure grammar 0.0016296890000000001
initial grammar 0.001618552
new word 0.001599505
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grammar precision 0.0015214450000000002
input grammar 0.001508795
lexicalized grammar 0.001506951
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grammar variables 0.001478802
minimal grammar 0.0014647080000000001
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word sequence 0.0014579719999999999
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categorial grammar 0.001440274
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grammar generalization 0.001414291
versal grammar 0.001414291
pos tags 0.00139599
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word bigram 0.0013782129999999999
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category ambiguity 0.0013640570000000001
development data 0.00135435
word tokens 0.0013535609999999999
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data yields 0.0013383800000000001
ccgbank data 0.001330959
data ccgbank 0.001330959
italian data 0.001320624
data settings 0.0013167550000000002
unlabeled data 0.001300953
standard set 0.0012887810000000001
same tagging 0.001270949
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same supertags 0.001260913
cth word 0.001256165
test corpus 0.0012463499999999998
tagging accuracy 0.001222177
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pos tagging 0.001218491
type category 0.001203992
such lexicon 0.001173055
grammar 0.00116871
ambiguous words 0.001160534
gold tags 0.001138551
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lexicon gold 0.001104119
lexical categories 0.00109642
common words 0.001093916
category associations 0.00108928
other derivations 0.001075331
