#22671This 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,24-1-A92-1027,ak
specific
<term>
information
</term>
from
<term>
unrestricted texts
</term>
where many of the
<term>
words
</term>
#22538We 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,30-1-A92-1027,ak
unrestricted texts
</term>
where many of the
<term>
words
</term>
are unknown and much of the
<term>
#22544We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of thewords are unknown and much of the text is irrelevant to the task.
other,25-4-A92-1027,ak
are introduced so that every final
<term>
constituent
</term>
covers the longest possible span
#22629The 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.
other,11-1-A92-1027,ak
phrase structure parsing
</term>
of
<term>
natural language
</term>
that is tailored to the problem of
#22525We 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.
tech,4-1-A92-1027,ak
presented . We present an efficient
<term>
algorithm
</term>
for
<term>
chart-based phrase structure
#22518We present an efficientalgorithm for chart-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,22-1-A92-1027,ak
the problem of extracting specific
<term>
information
</term>
from
<term>
unrestricted texts
</term>
#22536We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specificinformation from unrestricted texts where many of the words are unknown and much of the text is irrelevant to the task.
other,38-6-A92-1027,ak
number of
<term>
edges
</term>
, since only
<term>
edges
</term>
with a valid
<term>
semantic interpretation
#22712A 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,3-2-A92-1027,ak
task . The
<term>
parser
</term>
gains
<term>
algorithmic efficiency
</term>
through a reduction of its
<term>
search
#22561The parser gainsalgorithmic efficiency through a reduction of its search space.
other,2-4-A92-1027,ak
conventional treatments . The resulting
<term>
spanning edges
</term>
are insured to be the correct ones
#22606The 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,18-6-A92-1027,ak
<term>
syntactic categories
</term>
on the
<term>
terminal and non-terminal edges
</term>
, thereby reducing the amount of
<term>
#22692A further reduction in the search space is achieved by using semantic rather than syntactic categories on theterminal 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.
tech,6-1-A92-1027,ak
efficient
<term>
algorithm
</term>
for
<term>
chart-based phrase structure parsing
</term>
of
<term>
natural language
</term>
that
#22520We 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,5-6-A92-1027,ak
</term>
. A further reduction in the
<term>
search space
</term>
is achieved by using semantic rather
#22679A further reduction in thesearch 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,8-3-A92-1027,ak
new
<term>
edge
</term>
is added to the
<term>
chart
</term>
, the
<term>
algorithm
</term>
checks
#22579As each new edge is added to thechart, the algorithm checks only the topmost of the edges adjacent to it, rather than all such edges as in conventional treatments.
other,15-5-A92-1027,ak
heuristics
</term>
based on the placement of
<term>
function words
</term>
, and by
<term>
heuristic rules
</term>
#22651This 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,14-6-A92-1027,ak
achieved by using semantic rather than
<term>
syntactic categories
</term>
on the
<term>
terminal and non-terminal
#22688A 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.
model,20-5-A92-1027,ak
<term>
function words
</term>
, and by
<term>
heuristic rules
</term>
that permit certain kinds of
<term>
#22656This 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.
tech,1-2-A92-1027,ak
</term>
is irrelevant to the task . The
<term>
parser
</term>
gains
<term>
algorithmic efficiency
#22559Theparser gains algorithmic efficiency through a reduction of its search space.
model,7-5-A92-1027,ak
is facilitated through the use of
<term>
phrase boundary heuristics
</term>
based on the placement of
<term>
function
#22643This 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,42-6-A92-1027,ak
only
<term>
edges
</term>
with a valid
<term>
semantic interpretation
</term>
are ever introduced . In this paper
#22716A 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 only edges with a validsemantic interpretation are ever introduced.