W15-1704 |
during each iteration automated
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machine annotation
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is performed followed by manual
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C02-1083 |
differences between human and
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machine annotations
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( see figure 5 ) . Interval operations
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W04-1213 |
test of the limits of human and
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machine annotation
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capability . For the shared task
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W14-2513 |
correct more false positives in the
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machine annotations
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. For future work , we plan to
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W12-0105 |
future we plan to develop automatic
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machine annotations
|
for video sequences and compare
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W15-1704 |
the initial iteration automated
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machine annotations
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are produced using a gazetteer
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W05-0310 |
semantically rich , human-aided
|
machine annotation
|
system created within the Ontological
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W14-3109 |
correct an acceptable number of
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machine annotations
|
that are most likely to increase
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W14-2513 |
pick the most " prof - itable "
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machine annotations
|
to be corrected by human annotators
|
W14-3109 |
different sampling strategies of
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machine annotations
|
presented to human annotators
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W15-1704 |
model . Manual correction of the
|
machine annotations
|
involves : ( 1 ) removing incorrect
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W14-2513 |
and will evolve and improve as
|
machine annotations
|
that are verified by human annotators
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W14-2513 |
have human annotators correct
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machine annotations
|
in order to produce more examples
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N13-1088 |
scenarios to compare human and
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machine annotation
|
processes . An eye movement experiment
|
W14-3109 |
, and how the sample sizes of
|
machine annotations
|
affect ML perfor - mance . Also
|
W14-3109 |
known about the optimal number of
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machine annotations
|
to be presented to human annotators
|
W05-0310 |
Semantically Rich Human-Aided
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Machine Annotation
|
</title> Marjorie McShane Sergei
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W05-0310 |
semantically rich , human-aided
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machine annotation
|
( HAMA ) , implemented in the
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W05-0310 |
operation of the human - assisted
|
machine annotation
|
approach is enhancement of the
|