relation extraction 0.0034752900000000002
semantic relation 0.0032063250000000003
relation type 0.003200796
relation classification 0.0029365570000000002
relation types 0.0028715950000000002
single relation 0.0027728910000000004
likely relation 0.0027516270000000004
relation labeling 0.002750418
relation nodes 0.002744101
relation node 0.0027368270000000003
relation location 0.002706869
target relation 0.002704048
prevent relation 0.0026836530000000003
relation truth 0.002681924
relation clas 0.002681015
relation classifi 0.0026758380000000003
ditional relation 0.0026701890000000003
frequent relation 0.0026644090000000004
relation classifica 0.002659952
relation def 0.002658194
relation 0.00243747
semantic features 0.002041785
word features 0.001882364
semantic relations 0.001864265
other features 0.001818694
different features 0.001787994
entity extraction 0.0016786000000000001
only features 0.0016557870000000001
lexical features 0.001620575
different relations 0.001610474
single features 0.001608351
mesh features 0.001569026
following features 0.001566596
information extraction 0.001523801
extraction task 0.0015205000000000002
servable features 0.00149561
orthographic features 0.00149461
role extraction 0.001482882
graphical model 0.001418715
training data 0.001385888
possible relations 0.001372443
ent relations 0.001367571
discriminative model 0.0013633070000000002
static model 0.001358823
dynamic model 0.0013528510000000002
training set 0.00133924
model notation 0.001332335
criminative model 0.00132462
extraction tasks 0.0013215520000000001
again model 0.0013150560000000002
features 0.00127293
tity extraction 0.0012718920000000002
tomatic extraction 0.0012618990000000001
semantic entities 0.00126122
lationship extraction 0.0012584570000000002
learning algorithm 0.001218456
other words 0.00121028
single feature 0.001189315
important feature 0.0011519149999999999
medical subject 0.001109205
relations 0.00109541
model 0.00109364
relational learning 0.001091447
feature vec 0.001089016
tant feature 0.001076738
semantic constraints 0.001075334
such entities 0.0010649000000000001
medical ontology 0.001064234
semantic relationships 0.001061784
same entities 0.001047672
semantic roles 0.001044874
labeled data 0.001044636
extraction 0.00103782
generative models 0.001026529
relationship classification 0.0010245839999999998
semantic grammar 0.001010201
semantic categories 9.97353E-4
testing data 9.88558E-4
different domain 9.86634E-4
text classification 9.8529E-4
classification task 9.81767E-4
other types 9.79889E-4
specific words 9.669819999999999E-4
entity recognition 9.57392E-4
many role 9.429309999999999E-4
graphical models 9.38436E-4
domain knowledge 9.29843E-4
set error 9.22854E-4
classification problem 9.18329E-4
trigger word 9.09993E-4
tree algorithm 9.02977E-4
little training 9.00995E-4
classification accuracy 8.94342E-4
predicator words 8.86428E-4
discriminative models 8.83028E-4
ical models 8.82245E-4
static models 8.78544E-4
statistical models 8.74461E-4
dynamic models 8.725720000000001E-4
markov models 8.720819999999999E-4
