D15-1156 |
approach for machine learning-based
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empty category detection
|
that is based on the phrase structure
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N13-1125 |
zero anaphora resolution , where
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empty category detection
|
is a subtask . More recently
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D15-1156 |
Cai et al. ( 2011 ) integrated
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empty category detection
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with the syntactic parsing .
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P04-1082 |
provide a separate evaluation of the
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empty category detection
|
and resolution task . Johnson
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D15-1156 |
shows the accuracies of various
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empty category detection
|
methods , for both gold parse
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D15-1156 |
we proposed a novel model for
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empty category detection
|
in Japanese using path features
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D15-1156 |
another baseline . It formulates
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empty category detection
|
as the classification of IP nodes
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D15-1156 |
would be obviously useful for
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empty category detection
|
because it provides information
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W11-0417 |
sets of results , the overall
|
empty categories detection
|
along with the accuracies of
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D15-1156 |
shows the accuracies of Japanese
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empty category detection
|
, using the original and our
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N13-1125 |
Program . <title> Dependency-based
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empty category detection
|
via phrase structure trees </title>
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D15-1156 |
we propose a novel method for
|
empty category detection
|
for Japanese that uses conjunction
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D15-1156 |
detection with the syntactic parsing .
|
Empty category detection
|
for pro ( dropped pronouns or
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D15-1156 |
parser . Since the accuracy of the
|
empty category detection
|
implemented as a post-process
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D15-1156 |
Xiang et al. , 2013 ) for Chinese
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empty category detection
|
as well as linguistically-motivated
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D15-1156 |
2246/10 -1 FADeBaC ) . <title>
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Empty Category Detection
|
using Path Features and Distributed
|