S07-1065 |
word category information for
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verb disambiguation
|
. lNr V/v _ P/n Q/v JDV / ns
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S07-1065 |
word category information for
|
verb disambiguation
|
. 3.1 Basic Features Since the
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S07-1065 |
information of a Chinese thesaurus for
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verb disambiguation
|
. Note that we did not do any
|
S07-1065 |
important knowledge source for
|
verb disambiguation
|
. The word category information
|
S07-1065 |
Chinese thesaurus as features for
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verb disambiguation
|
. For the task we participated
|
C04-1131 |
improves the precision of the
|
verbs disambiguation
|
by 0.75 % in average . word ?
|
J03-4004 |
Previously , we evaluated noun and
|
verb disambiguation
|
on the English all-words task
|
P06-2119 |
context of each instance . Noun and
|
verb disambiguation
|
results are respectively displayed
|
P98-1082 |
1993 ) is used as a bootstrap for
|
verb disambiguation
|
. They tune it to the domain
|
D14-1079 |
Disambiguation We use the transitive
|
verb disambiguation
|
dataset described in Grefenstette
|
P10-1124 |
for a supervised classifier in a
|
verb disambiguation
|
task . Training set generation
|
J12-1003 |
for a supervised classifier in a
|
verb disambiguation
|
task . ( 4 ) Training a classifier
|
D14-1079 |
approaches ) in tasks involving
|
verb disambiguation
|
and sentence similarity . To
|
S10-1088 |
performance was not better than the
|
verb disambiguation
|
performance as was expected .
|
D14-1079 |
composition performed best with the
|
verb disambiguation
|
task , where the verb senses
|
P15-2120 |
SVO similarity judgements on the
|
verb disambiguation
|
( GS11 ) and sentence similarity
|
P06-2119 |
transformations using EAT for
|
verb disambiguation
|
are significantly better than
|
P13-2096 |
problems in NLP , and in WSD ,
|
verb disambiguation
|
has proved to be extremely difficult
|
D13-1166 |
training on average per dataset . 8.1
|
Verb disambiguation
|
task Perhaps surprisingly , one
|
C04-1131 |
cases , and in particular for
|
verbs disambiguation
|
. Table 3 informs us about the
|