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ccg lexicon 0.001781159
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ccg system 0.0016863590000000001
logical meaning 0.001681577
lexical entries 0.0016487339999999998
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ccg grammar 0.001633726
grammar ccg 0.001633726
semantic type 0.0016214469999999998
parsing model 0.001619331
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ccg parsing 0.001606771
semantic parse 0.001589255
training set 0.001562787
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single ccg 0.001499626
lexical templates 0.001470827
lexical item 0.001463379
logical expression 0.0014611889999999999
function word 0.001427491
lexical entry 0.001422767
training example 0.0014203129999999999
lexical induction 0.001415946
lexical items 0.001403634
logical expressions 0.0013782339999999999
learning problems 0.0013753329999999999
data set 0.0013710710000000002
ccg categories 0.0013537290000000001
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lexical variation 0.001347938
complete learning 0.001343828
learning rate 0.001342533
semantic derivations 0.0013370489999999999
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logical forms 0.00132471
ccg grammars 0.001322042
initial model 0.001304339
single language 0.001282639
semantic information 0.001280456
online learning 0.00127917
ccg induction 0.001271816
ccg combinators 0.001266958
generative model 0.001262066
ccg operator 0.001259558
probabilistic ccg 0.001257811
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related learning 0.001250512
full set 0.001248428
splitting ccg 0.001248082
training data 0.001241782
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training sentence 0.0012376420000000002
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sentence new 0.0012373850000000001
test set 0.00123329
logical repre 0.0012225019999999999
semantic parsers 0.001222215
ccg cat 0.001218844
semantic content 0.001218064
ibm model 0.001214748
semantic fea 0.001212966
logical connectors 0.0012083509999999999
semantic representa 0.0012027659999999999
ccg syn 0.001201975
ubl learning 0.001199885
semantic informa 0.001199255
learning regularities 0.0011963949999999998
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language sentences 0.0011752989999999999
possible parses 0.0011639620000000002
natural language 0.001157106
function types 0.001140361
function application 0.001136838
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empty set 0.001131026
development set 0.00112789
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training pairs 0.001122128
recent approach 0.0011210389999999999
different meaning 0.001118006
possible split 0.001114683
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lexical 0.00111039
form representations 0.001108926
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labeled meaning 0.001096786
feature vector 0.001093942
new york 0.001091717
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new variables 0.001090655
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meaning representation 0.0010900390000000001
meaning representations 0.001087619
update lexicon 0.001086119
universal set 0.0010819760000000001
system english 0.0010620270000000001
input type 0.001059351
correct parse 0.001051125
