Analysis of the results shows that each component of the
<term>
system
</term>
contributed to the
<term>
scores
</term>
.
<term>
Parallel wordnets
</term>
built upon correspondences between different
<term>
languages
</term>
can play a crucial role in
<term>
multilingual knowledge processing
</term>
.
#7055Analysis of the results shows that each component of the system contributed to the scores.Parallel wordnets built upon correspondences between different languages can play a crucial role in multilingual knowledge processing.
lr,12-3-I05-4007,ak
In this paper , we propose and implement a model for bootstrapping
<term>
parallel wordnets
</term>
based on one
<term>
monolingual wordnet
</term>
and a set of
<term>
cross-lingual lexical semantic relations
</term>
.
#7112In this paper, we propose and implement a model for bootstrappingparallel wordnets based on one monolingual wordnet and a set of cross-lingual lexical semantic relations.
lr,17-3-I05-4007,ak
In this paper , we propose and implement a model for bootstrapping
<term>
parallel wordnets
</term>
based on one
<term>
monolingual wordnet
</term>
and a set of
<term>
cross-lingual lexical semantic relations
</term>
.
#7117In this paper, we propose and implement a model for bootstrapping parallel wordnets based on onemonolingual wordnet and a set of cross-lingual lexical semantic relations.
lr,17-4-I05-4007,ak
In particular , we propose a set of
<term>
inference rules
</term>
to predict
<term>
Chinese wordnet structure
</term>
based on
<term>
English wordnet
</term>
and
<term>
English-Chinese translation relations
</term>
.
#7145In particular, we propose a set of inference rules to predict Chinese wordnet structure based onEnglish wordnet and English-Chinese translation relations.
lr,8-2-I05-4007,ak
Since there is no
<term>
homomorphism
</term>
between pairs of
<term>
monolingual wordnets
</term>
, we must rely on
<term>
lexical semantic relation ( LSR ) mappings
</term>
to ensure
<term>
conceptual cohesion
</term>
.
#7081Since there is no homomorphism between pairs ofmonolingual wordnets, we must rely on lexical semantic relation (LSR) mappings to ensure conceptual cohesion.
measure(ment),14-5-I05-4007,ak
We show that this model of
<term>
parallel wordnet building
</term>
is effective and achieves higher
<term>
precision
</term>
in
<term>
LSR prediction
</term>
.
#7166We show that this model of parallel wordnet building is effective and achieves higherprecision in LSR prediction.
model,15-2-I05-4007,ak
Since there is no
<term>
homomorphism
</term>
between pairs of
<term>
monolingual wordnets
</term>
, we must rely on
<term>
lexical semantic relation ( LSR ) mappings
</term>
to ensure
<term>
conceptual cohesion
</term>
.
#7088Since there is no homomorphism between pairs of monolingual wordnets, we must rely onlexical semantic relation ( LSR ) mappings to ensure conceptual cohesion.
model,23-3-I05-4007,ak
In this paper , we propose and implement a model for bootstrapping
<term>
parallel wordnets
</term>
based on one
<term>
monolingual wordnet
</term>
and a set of
<term>
cross-lingual lexical semantic relations
</term>
.
#7123In this paper, we propose and implement a model for bootstrapping parallel wordnets based on one monolingual wordnet and a set ofcross-lingual lexical semantic relations.
model,8-4-I05-4007,ak
In particular , we propose a set of
<term>
inference rules
</term>
to predict
<term>
Chinese wordnet structure
</term>
based on
<term>
English wordnet
</term>
and
<term>
English-Chinese translation relations
</term>
.
#7136In particular, we propose a set ofinference rules to predict Chinese wordnet structure based on English wordnet and English-Chinese translation relations.
other,12-4-I05-4007,ak
In particular , we propose a set of
<term>
inference rules
</term>
to predict
<term>
Chinese wordnet structure
</term>
based on
<term>
English wordnet
</term>
and
<term>
English-Chinese translation relations
</term>
.
#7140In particular, we propose a set of inference rules to predictChinese wordnet structure based on English wordnet and English-Chinese translation relations.
other,20-4-I05-4007,ak
In particular , we propose a set of
<term>
inference rules
</term>
to predict
<term>
Chinese wordnet structure
</term>
based on
<term>
English wordnet
</term>
and
<term>
English-Chinese translation relations
</term>
.
#7148In particular, we propose a set of inference rules to predict Chinese wordnet structure based on English wordnet andEnglish-Chinese translation relations.
other,24-2-I05-4007,ak
Since there is no
<term>
homomorphism
</term>
between pairs of
<term>
monolingual wordnets
</term>
, we must rely on
<term>
lexical semantic relation ( LSR ) mappings
</term>
to ensure
<term>
conceptual cohesion
</term>
.
#7097Since there is no homomorphism between pairs of monolingual wordnets, we must rely on lexical semantic relation (LSR) mappings to ensureconceptual cohesion.
other,4-2-I05-4007,ak
Since there is no
<term>
homomorphism
</term>
between pairs of
<term>
monolingual wordnets
</term>
, we must rely on
<term>
lexical semantic relation ( LSR ) mappings
</term>
to ensure
<term>
conceptual cohesion
</term>
.
#7077Since there is nohomomorphism between pairs of monolingual wordnets, we must rely on lexical semantic relation (LSR) mappings to ensure conceptual cohesion.
other,7-1-I05-4007,ak
<term>
Parallel wordnets
</term>
built upon correspondences between different
<term>
languages
</term>
can play a crucial role in
<term>
multilingual knowledge processing
</term>
.
#7062Parallel wordnets built upon correspondences between differentlanguages can play a crucial role in multilingual knowledge processing.
tech,14-1-I05-4007,ak
<term>
Parallel wordnets
</term>
built upon correspondences between different
<term>
languages
</term>
can play a crucial role in
<term>
multilingual knowledge processing
</term>
.
#7069Parallel wordnets built upon correspondences between different languages can play a crucial role inmultilingual knowledge processing.
tech,16-5-I05-4007,ak
We show that this model of
<term>
parallel wordnet building
</term>
is effective and achieves higher
<term>
precision
</term>
in
<term>
LSR prediction
</term>
.
#7168We show that this model of parallel wordnet building is effective and achieves higher precision inLSR prediction.
tech,6-5-I05-4007,ak
We show that this model of
<term>
parallel wordnet building
</term>
is effective and achieves higher
<term>
precision
</term>
in
<term>
LSR prediction
</term>
.
#7158We show that this model ofparallel wordnet building is effective and achieves higher precision in LSR prediction.