training data 0.002267663
crf model 0.002006466
test data 0.0019788289999999997
ing data 0.0018815379999999999
pos tag 0.001796546
sequence model 0.001777738
labeled data 0.001762188
word type 0.001759055
pos labels 0.0017372619999999998
annotated data 0.001737048
linear model 0.0017203689999999998
supervision data 0.001700291
pos information 0.0016505320000000001
target word 0.0016206900000000002
allel data 0.001615751
pos tags 0.0016064130000000001
tag set 0.001565861
feature set 0.001524636
different annotation 0.001522001
word alignments 0.001520273
function words 0.001514996
training algorithm 0.001493482
several pos 0.0014781080000000001
several language 0.001466533
pos tagset 0.001408637
model 0.00138931
pos transfer 0.001382705
label transfer 0.001374951
source language 0.001374534
pos tagger 0.001371076
target language 0.001365799
tag dictionary 0.001364531
training parallel 0.001357109
different domain 0.001351575
test set 0.001313518
training method 0.001311569
possible labels 0.001291075
correct label 0.001289179
gold label 0.0012804589999999999
test tags 0.001270448
source words 0.001264062
target words 0.001255327
different models 0.001253246
supervised learning 0.0012387090000000002
label ambiguity 0.001233906
pos taggers 0.001231339
training procedure 0.001228799
universal pos 0.001223524
second tag 0.001214581
training part 0.001214074
syntactic information 0.0012042210000000001
type constraints 0.0011964620000000001
same setting 0.0011951800000000001
efficient pos 0.00118991
tag distribution 0.001184412
language structure 0.001182933
matched pos 0.001173948
language families 0.001166751
possible tags 0.0011602259999999999
annotation mismatch 0.001156627
correct labels 0.001154027
training samples 0.001148341
gold labels 0.001145307
annotation conventions 0.00114393
projected labels 0.001132861
other alignment 0.00112032
whole tag 0.001115713
token constraints 0.00110652
arbitrary annotation 0.001104989
learning techniques 0.001101534
contradictory annotation 0.0011000670000000001
supervised models 0.001095465
joint feature 0.001092276
feature map 0.001072764
additional information 0.001071759
test time 0.001053277
novel learning 0.001051587
same train 0.001045983
ble labels 0.001036785
supervision information 0.001036029
dicted labels 0.001033518
machine learning 0.001032762
uncertain labels 0.001032638
ambiguous learning 0.001024583
alternative learning 0.001020342
gold tags 0.001014458
information sources 0.0010015
ing error 9.98338E-4
ambiguous set 9.95854E-4
standard error 9.95095E-4
domain mismatch 9.86201E-4
crf baseline 9.80313E-4
learning methodology 9.75237E-4
test sets 9.5209E-4
supervised setting 9.48384E-4
linear crf 9.48215E-4
other cases 9.470079999999999E-4
gual information 9.45744E-4
other categories 9.399619999999999E-4
label 9.3233E-4
