P11-2035 |
opportunity for large-scale , robust
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parser combination
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. 5 Conclusion We have presented
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P09-2010 |
locate the pre cise benefits of the
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parser combination
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. We will also investigate the
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P07-1079 |
accuracy simply by using an existing
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parser combination
|
approach . As a first step ,
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N09-2066 |
new linear algorithm to perform
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parser combination
|
. Experiments on the corpora
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N09-2064 |
improve upon existing methods for
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parser combination
|
. First , we propose a method
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P07-1079 |
experiments on development data using
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parser combinations
|
to produce dependency constraints
|
D09-1161 |
confidence " was used in prior
|
parser combination
|
studies to refer to the accuracy
|
N09-2064 |
improve upon existing methods for
|
parser combination
|
. First , while constituent recombination
|
N09-2064 |
framework . Third , we extend these
|
parser combination
|
methods from 1-best outputs to
|
N09-2064 |
selection . Third , we extend these
|
parser combination
|
methods from multiple 1-best
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N06-2033 |
<authors></authors> Abstract We present a novel
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parser combination
|
scheme that works by reparsing
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D08-1017 |
reinterpreting and generalizing their
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parser combination
|
scheme as a stacking of parsers
|
D12-1105 |
in effect , a simple method for
|
parser combination
|
, not all that dissimilar to
|
N09-2066 |
are obtained by using a linear
|
parser combination
|
algorithm on the outputs of three
|
P07-1079 |
in previous work on dependency
|
parser combination
|
( Zeman and ˇZabokrtsk ´
|
N09-2066 |
2007 Shared Task , the linear
|
parser combination
|
achieves the best LAS for Czech
|
N10-1091 |
Experiments 3.1 On scoring models for
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parser combination
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The most common approach for
|
P10-1110 |
learning ( Koo et al. , 2008 ) and
|
parser combination
|
( Zhang and Clark , 2008 ) do
|
N06-2033 |
No . HR0011-06-C-0023 . <title>
|
Parser Combination
|
by Reparsing Sagae Language Technologies
|
N10-1091 |
learning time , we argue that runtime
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parser combination
|
is a more attractive approach
|