concept graph 0.002354149
amr graph 0.001971578
candidate graph 0.0017859249999999998
directed graph 0.0017786109999999998
connected graph 0.0017776139999999998
dense graph 0.0017581069999999999
word sense 0.001703437
graph fragment 0.0016957959999999998
graph fragments 0.0016814269999999999
input graph 0.0016769929999999999
empty graph 0.0016475449999999998
graph frag 0.001636891
acyclic graph 0.0016338239999999999
graph transduc 0.0016307499999999998
semantic dependency 0.0015791689999999998
semantic parsing 0.0014998989999999999
word sequence 0.0014350279999999999
graph 0.00142725
matching word 0.0014272339999999999
head word 0.0014174189999999998
tail word 0.0014160359999999999
training data 0.0014049560000000002
edge set 0.001376964
word ending 0.001371354
canonical word 0.001371354
chinese word 0.001371354
word segmenta 0.001371354
semantic role 0.0013683769999999998
semantic argument 0.001354894
concept label 0.001324679
semantic phenomena 0.001314313
semantic formalism 0.001312873
semantic parsers 0.001312169
single concept 0.001290988
core algorithm 0.0012864819999999998
concept node 0.00128499
tree algorithm 0.00127816
concept identification 0.00126106
labeled concept 0.00124087
dependency edge 0.001237482
ing concept 0.00122661
test data 0.001209514
concept fragment 0.001195445
common concept 0.001195232
concept subgraph 0.001190868
concept fragments 0.001181076
head concept 0.001178058
programming algorithm 0.0011779849999999999
tail concept 0.001176675
concept lexicon 0.001174329
concept types 0.001151443
special concept 0.0011498980000000001
mscg algorithm 0.0011480409999999998
concept labeling 0.001147723
unaligned concept 0.001141656
concept frag 0.0011365400000000001
subgraph algorithm 0.001133449
concept identifica 0.001133398
concept identifi 0.001130119
concept identifier 0.001130119
invoked concept 0.001130119
data structure 0.001125553
novel algorithm 0.0011220099999999999
run algorithm 0.001121569
algorithm the 0.001110004
ing data 0.001097343
approximate algorithm 0.001093244
labeling algorithm 0.0010903039999999998
viterbi algorithm 0.001079577
labeled edge 0.001077824
edge scores 0.001072148
next edge 0.001069846
outgoing edge 0.001059098
small set 0.001054556
other edges 0.001047683
polarity edge 0.001040955
degree edge 0.001039275
edge labels 0.001031997
constraint set 0.001031677
training corpus 0.001029661
unit edge 0.00102674
test set 0.001024993
amr graphs 0.0010167919999999999
system concepts 0.001008002
new feature 0.001004589
name edge 0.001003866
edge weights 0.001001109
positive edge 9.98292E-4
sentences tokens 9.97055E-4
self edge 9.79177E-4
negative edge 9.7311E-4
other node 9.69576E-4
cus edge 9.68358E-4
feature vector 9.51496E-4
distance feature 9.46205E-4
other vertex 9.44175E-4
english language 9.41552E-4
identification training 9.414849999999999E-4
amr parsing 9.386869999999999E-4
first approach 9.30253E-4
