A97-1022 |
design of grammar for positive
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projective parsing
|
. The core idea of this approach
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E06-1011 |
projective parsers using the exact
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projective parsing
|
algorithms . The purpose of these
|
E12-1042 |
si , sj ) Ey using the standard
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projective parsing
|
algorithm for arc-factored models
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E06-1011 |
to use a O ( n3 ) second-order
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projective parsing
|
algorithm , as we will see later
|
E14-4031 |
uses 1st-order features , and a
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projective parsing
|
algorithm with 5-best MIRA training
|
D14-1099 |
These oracles are all defined for
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projective parsing
|
. In this paper , we present
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D08-1017 |
approximation based on O ( n3 )
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projective parsing
|
followed by rearrangement to
|
D08-1016 |
raise the polynomial runtime of
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projective parsing
|
, and render non-projective parsing
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D09-1004 |
McDonald et al. , 2006 ) with
|
projective parsing
|
. Moreover , we exploit three
|
J08-4003 |
parsing technique to a strictly
|
projective parsing
|
algorithm . Moreover , despite
|
D14-1099 |
this enhancement is limited to
|
projective parsing
|
, and dynamic oracles have not
|
D11-1114 |
has been successfully used for
|
projective parsing
|
( Huang and Sagae , 2010 ; Kuhlmann
|
D13-1152 |
iterations in our firstorder dynamic
|
projective parsing
|
. From iterations 1 to 6 , we
|
D13-1152 |
c ) , we can not afford to run
|
projective parsing
|
multiple times . The single resulting
|
D13-1152 |
runtime -- the same as one call to
|
projective parsing
|
, and far faster in prac - tice
|
E12-2012 |
projective version of Covington 's
|
projective parsing
|
algorithm and the projective
|
J08-4003 |
combination with an essentially
|
projective parsing
|
algo - rithm . Finally , we have
|
D13-1152 |
information via a coarse-to-fine
|
projective parsing
|
cas cade ( Charniak et al. ,
|
J08-4003 |
complexity is O ( n ) . ■ 5.2
|
Projective Parsing
|
The transition set T for the
|
E06-1011 |
already been found by the exact
|
projective parsing
|
algorithm . It is not difficult
|