W15-5412 |
provides 100 % accuracy on language
|
group identification
|
. Regarding language labelling
|
J91-3001 |
of the output of the language
|
group identification
|
module . The table consists of
|
W03-0505 |
category . Scores for main verb
|
group identification
|
are presented below in the results
|
W03-0505 |
of a verb group . The main verb
|
group identification
|
algorithm considers only verb
|
W15-5408 |
identification accuracy at the
|
group identification
|
phase . After the shared task
|
N13-1123 |
observed for the task of user
|
group identification
|
. We also perform the 2-tailed
|
W00-0401 |
processing including noun and verb
|
group identification
|
and conceptual tagging . The
|
J02-4005 |
method relies on noun and verb
|
group identification
|
, conceptual tagging , pattern
|
W15-5408 |
optimize the units used in the
|
group identification
|
phase and we ended up using character
|
J02-4005 |
0 of the section ) , only noun
|
group identification
|
is carried out in those components
|
W95-0107 |
focused primarily on low-level noun
|
group identification
|
, frequently as a step in deriving
|
W15-5412 |
shows 100 % accuracy on language
|
group identification
|
and 93.66 % accuracy on language
|
W15-5408 |
from the excerpts . 3.2 Language
|
group identification
|
We followed the example given
|
E14-1012 |
different gangs signal within -
|
group identification
|
and across-group animosity or
|
P09-2009 |
handling of suffixes , accurate verb
|
group identification
|
and learning of disambiguation
|
P12-3023 |
. Part-ofspeech tagging , noun
|
group identification
|
, named entity recognition ,
|