tech,7-2-A92-1027,bq |
gains algorithmic efficiency through a
<term>
|
reduction
|
</term>
of its
<term>
search space
</term>
.
|
#17594
The parser gains algorithmic efficiency through areduction of its search space. |
other,20-5-A92-1027,bq |
<term>
function words
</term>
, and by
<term>
|
heuristic rules
|
</term>
that permit certain kinds of
<term>
|
#17685
This is facilitated through the use of phrase boundary heuristics based on the placement of function words, and byheuristic rules that permit certain kinds of phrases to be deduced despite the presence of unknown words. |
other,25-4-A92-1027,bq |
are introduced so that every final
<term>
|
constituent
|
</term>
covers the longest possible
<term>
|
#17658
The resulting spanning edges are insured to be the correct ones by carefully controlling the order in which edges are introduced so that every finalconstituent covers the longest possible span. |
tech,6-1-A92-1027,bq |
present an efficient algorithm for
<term>
|
chart-based phrase structure parsing
|
</term>
of
<term>
natural language
</term>
that
|
#17549
We present an efficient algorithm forchart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task. |
other,24-1-A92-1027,bq |
extracting specific information from
<term>
|
unrestricted texts
|
</term>
where many of the
<term>
words
</term>
|
#17567
We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information fromunrestricted texts where many of the words are unknown and much of the text is irrelevant to the task. |
other,2-6-A92-1027,bq |
<term>
unknown words
</term>
. A further
<term>
|
reduction in the search space
|
</term>
is achieved by using
<term>
semantic
|
#17705
A furtherreduction in the search space is achieved by using semantic rather than syntactic categories on the terminal and non-terminal edges, thereby reducing the amount of ambiguity and thus the number of edges, since only edges with a valid semantic interpretation are ever introduced. |
other,10-2-A92-1027,bq |
through a
<term>
reduction
</term>
of its
<term>
|
search space
|
</term>
. As each new
<term>
edge
</term>
is
|
#17597
The parser gains algorithmic efficiency through a reduction of itssearch space. |
other,3-3-A92-1027,bq |
<term>
search space
</term>
. As each new
<term>
|
edge
|
</term>
is added to the
<term>
chart
</term>
|
#17603
As each newedge is added to the chart, the algorithm checks only the topmost of the edges adjacent to it, rather than all such edges as in conventional treatments. |
other,28-6-A92-1027,bq |
</term>
, thereby reducing the amount of
<term>
|
ambiguity
|
</term>
and thus the number of
<term>
edges
|
#17731
A further reduction in the search space is achieved by using semantic rather than syntactic categories on the terminal and non-terminal edges, thereby reducing the amount ofambiguity and thus the number of edges, since only edges with a valid semantic interpretation are ever introduced. |
other,27-5-A92-1027,bq |
</term>
that permit certain kinds of
<term>
|
phrases
|
</term>
to be deduced despite the presence
|
#17692
This is facilitated through the use of phrase boundary heuristics based on the placement of function words, and by heuristic rules that permit certain kinds ofphrases to be deduced despite the presence of unknown words. |
other,34-6-A92-1027,bq |
ambiguity
</term>
and thus the number of
<term>
|
edges
|
</term>
, since only
<term>
edges
</term>
with
|
#17737
A further reduction in the search space is achieved by using semantic rather than syntactic categories on the terminal and non-terminal edges, thereby reducing the amount of ambiguity and thus the number ofedges, since only edges with a valid semantic interpretation are ever introduced. |
other,11-1-A92-1027,bq |
phrase structure parsing
</term>
of
<term>
|
natural language
|
</term>
that is tailored to the problem of
|
#17554
We present an efficient algorithm for chart-based phrase structure parsing ofnatural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task. |
other,15-5-A92-1027,bq |
heuristics
</term>
based on the placement of
<term>
|
function words
|
</term>
, and by
<term>
heuristic rules
</term>
|
#17680
This is facilitated through the use of phrase boundary heuristics based on the placement offunction words, and by heuristic rules that permit certain kinds of phrases to be deduced despite the presence of unknown words. |
other,35-5-A92-1027,bq |
be deduced despite the presence of
<term>
|
unknown words
|
</term>
. A further
<term>
reduction in the
|
#17700
This is facilitated through the use of phrase boundary heuristics based on the placement of function words, and by heuristic rules that permit certain kinds of phrases to be deduced despite the presence ofunknown words. |
other,7-5-A92-1027,bq |
is facilitated through the use of
<term>
|
phrase boundary heuristics
|
</term>
based on the placement of
<term>
function
|
#17672
This is facilitated through the use ofphrase boundary heuristics based on the placement of function words, and by heuristic rules that permit certain kinds of phrases to be deduced despite the presence of unknown words. |
other,38-6-A92-1027,bq |
number of
<term>
edges
</term>
, since only
<term>
|
edges
|
</term>
with a valid
<term>
semantic
</term>
|
#17741
A further reduction in the search space is achieved by using semantic rather than syntactic categories on the terminal and non-terminal edges, thereby reducing the amount of ambiguity and thus the number of edges, since onlyedges with a valid semantic interpretation are ever introduced. |
other,30-4-A92-1027,bq |
</term>
covers the longest possible
<term>
|
span
|
</term>
. This is facilitated through the
|
#17663
The resulting spanning edges are insured to be the correct ones by carefully controlling the order in which edges are introduced so that every final constituent covers the longest possiblespan. |
other,2-4-A92-1027,bq |
conventional treatments . The resulting
<term>
|
spanning edges
|
</term>
are insured to be the correct ones
|
#17635
The resultingspanning edges are insured to be the correct ones by carefully controlling the order in which edges are introduced so that every final constituent covers the longest possible span. |
other,27-3-A92-1027,bq |
adjacent to it , rather than all such
<term>
|
edges
|
</term>
as in conventional treatments . The
|
#17627
As each new edge is added to the chart, the algorithm checks only the topmost of the edges adjacent to it, rather than all suchedges as in conventional treatments. |
other,14-6-A92-1027,bq |
using
<term>
semantic
</term>
rather than
<term>
|
syntactic categories
|
</term>
on the
<term>
terminal and non-terminal
|
#17717
A further reduction in the search space is achieved by using semantic rather thansyntactic categories on the terminal and non-terminal edges, thereby reducing the amount of ambiguity and thus the number of edges, since only edges with a valid semantic interpretation are ever introduced. |