other,7-1-P06-1052,bq |
present an efficient algorithm for the
<term>
|
redundancy elimination problem
|
</term>
: Given an
<term>
underspecified semantic
|
#11125
We present an efficient algorithm for theredundancy elimination problem: Given an underspecified semantic representation (USR) of a scope ambiguity, compute an USR with fewer mutually equivalent readings. |
other,13-1-P06-1052,bq |
elimination problem
</term>
: Given an
<term>
|
underspecified semantic representation ( USR )
|
</term>
of a
<term>
scope ambiguity
</term>
,
|
#11131
We present an efficient algorithm for the redundancy elimination problem: Given anunderspecified semantic representation ( USR ) of a scope ambiguity, compute an USR with fewer mutually equivalent readings. |
other,21-1-P06-1052,bq |
representation ( USR )
</term>
of a
<term>
|
scope ambiguity
|
</term>
, compute an
<term>
USR
</term>
with
|
#11139
We present an efficient algorithm for the redundancy elimination problem: Given an underspecified semantic representation (USR) of ascope ambiguity, compute an USR with fewer mutually equivalent readings. |
other,26-1-P06-1052,bq |
scope ambiguity
</term>
, compute an
<term>
|
USR
|
</term>
with fewer mutually
<term>
equivalent
|
#11144
We present an efficient algorithm for the redundancy elimination problem: Given an underspecified semantic representation (USR) of a scope ambiguity, compute anUSR with fewer mutually equivalent readings. |
other,30-1-P06-1052,bq |
<term>
USR
</term>
with fewer mutually
<term>
|
equivalent readings
|
</term>
. The algorithm operates on
<term>
|
#11148
We present an efficient algorithm for the redundancy elimination problem: Given an underspecified semantic representation (USR) of a scope ambiguity, compute an USR with fewer mutuallyequivalent readings. |
other,4-2-P06-1052,bq |
</term>
. The algorithm operates on
<term>
|
underspecified chart representations
|
</term>
which are derived from
<term>
dominance
|
#11155
The algorithm operates onunderspecified chart representations which are derived from dominance graphs; it can be applied to the USRs computed by large-scale grammars. |
other,11-2-P06-1052,bq |
representations
</term>
which are derived from
<term>
|
dominance graphs
|
</term>
; it can be applied to the
<term>
USRs
|
#11162
The algorithm operates on underspecified chart representations which are derived fromdominance graphs; it can be applied to the USRs computed by large-scale grammars. |
other,20-2-P06-1052,bq |
graphs
</term>
; it can be applied to the
<term>
|
USRs
|
</term>
computed by
<term>
large-scale grammars
|
#11171
The algorithm operates on underspecified chart representations which are derived from dominance graphs; it can be applied to theUSRs computed by large-scale grammars. |
other,23-2-P06-1052,bq |
to the
<term>
USRs
</term>
computed by
<term>
|
large-scale grammars
|
</term>
. We evaluate the algorithm on a
<term>
|
#11174
The algorithm operates on underspecified chart representations which are derived from dominance graphs; it can be applied to the USRs computed bylarge-scale grammars. |
lr,6-3-P06-1052,bq |
</term>
. We evaluate the algorithm on a
<term>
|
corpus
|
</term>
, and show that it reduces the degree
|
#11183
We evaluate the algorithm on acorpus, and show that it reduces the degree of ambiguity significantly while taking negligible runtime. |
other,16-3-P06-1052,bq |
show that it reduces the degree of
<term>
|
ambiguity
|
</term>
significantly while taking negligible
|
#11193
We evaluate the algorithm on a corpus, and show that it reduces the degree ofambiguity significantly while taking negligible runtime. |