other,71P061052,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,131P061052,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,211P061052,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,261P061052,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,301P061052,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,42P061052,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 largescale grammars. 
other,112P061052,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 largescale grammars. 
other,202P061052,bq 
graphs
</term>
; it can be applied to the
<term>

USRs

</term>
computed by
<term>
largescale grammars

#11171
The algorithm operates on underspecified chart representations which are derived from dominance graphs; it can be applied to theUSRs computed by largescale grammars. 
other,232P061052,bq 
to the
<term>
USRs
</term>
computed by
<term>

largescale 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 bylargescale grammars. 
lr,63P061052,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,163P061052,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. 