other,1-4-P82-1035,bq |
These
<term>
syntactic and semantic expectations
</term>
can be used to figure out
<term>
unknown words
</term>
from
<term>
context
</term>
, constrain the possible
<term>
word-senses
</term>
of
<term>
words with multiple meanings
</term>
(
<term>
ambiguity
</term>
) , fill in
<term>
missing words
</term>
(
<term>
elllpsis
</term>
) , and resolve
<term>
referents
</term>
(
<term>
anaphora
</term>
) .
|
#13056
Thesesyntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (elllpsis), and resolve referents (anaphora). |
other,6-2-P82-1035,bq |
However , a great deal of
<term>
natural language texts
</term>
e.g. ,
<term>
memos
</term>
, rough
<term>
drafts
</term>
,
<term>
conversation transcripts
</term>
etc. , have features that differ significantly from
<term>
neat texts
</term>
, posing special problems for readers , such as
<term>
misspelled words
</term>
,
<term>
missing words
</term>
,
<term>
poor syntactic construction
</term>
,
<term>
missing periods
</term>
, etc .
|
#12980
However, a great deal ofnatural language texts e.g., memos, rough drafts, conversation transcripts etc., have features that differ significantly from neat texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, missing periods, etc. |
other,16-2-P82-1035,bq |
However , a great deal of
<term>
natural language texts
</term>
e.g. ,
<term>
memos
</term>
, rough
<term>
drafts
</term>
,
<term>
conversation transcripts
</term>
etc. , have features that differ significantly from
<term>
neat texts
</term>
, posing special problems for readers , such as
<term>
misspelled words
</term>
,
<term>
missing words
</term>
,
<term>
poor syntactic construction
</term>
,
<term>
missing periods
</term>
, etc .
|
#12990
However, a great deal of natural language texts e.g., memos, rough drafts,conversation transcripts etc., have features that differ significantly from neat texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, missing periods, etc. |
other,11-4-P82-1035,bq |
These
<term>
syntactic and semantic expectations
</term>
can be used to figure out
<term>
unknown words
</term>
from
<term>
context
</term>
, constrain the possible
<term>
word-senses
</term>
of
<term>
words with multiple meanings
</term>
(
<term>
ambiguity
</term>
) , fill in
<term>
missing words
</term>
(
<term>
elllpsis
</term>
) , and resolve
<term>
referents
</term>
(
<term>
anaphora
</term>
) .
|
#13066
These syntactic and semantic expectations can be used to figure outunknown words from context, constrain the possible word-senses of words with multiple meanings (ambiguity), fill in missing words (elllpsis), and resolve referents (anaphora). |
other,10-5-P82-1035,bq |
This method of using
<term>
expectations
</term>
to aid the understanding of
<term>
scruffy texts
</term>
has been incorporated into a working
<term>
computer program
</term>
called
<term>
NOMAD
</term>
, which understands
<term>
scruffy texts
</term>
in the domain of Navy messages .
|
#13109
This method of using expectations to aid the understanding ofscruffy texts has been incorporated into a working computer program called NOMAD, which understands scruffy texts in the domain of Navy messages. |
tech,2-1-P82-1035,bq |
Most large
<term>
text-understanding systems
</term>
have been designed under the assumption that the input
<term>
text
</term>
will be in reasonably neat form , e.g. ,
<term>
newspaper stories
</term>
and other
<term>
edited texts
</term>
.
|
#12946
Most largetext-understanding systems have been designed under the assumption that the input text will be in reasonably neat form, e.g., newspaper stories and other edited texts. |
other,25-5-P82-1035,bq |
This method of using
<term>
expectations
</term>
to aid the understanding of
<term>
scruffy texts
</term>
has been incorporated into a working
<term>
computer program
</term>
called
<term>
NOMAD
</term>
, which understands
<term>
scruffy texts
</term>
in the domain of Navy messages .
|
#13124
This method of using expectations to aid the understanding of scruffy texts has been incorporated into a working computer program called NOMAD, which understandsscruffy texts in the domain of Navy messages. |
other,21-3-P82-1035,bq |
Our solution to these problems is to make use of
<term>
expectations
</term>
, based both on knowledge of
<term>
surface English
</term>
and on
<term>
world knowledge
</term>
of the situation being described .
|
#13047
Our solution to these problems is to make use of expectations, based both on knowledge of surface English and onworld knowledge of the situation being described. |
other,19-4-P82-1035,bq |
These
<term>
syntactic and semantic expectations
</term>
can be used to figure out
<term>
unknown words
</term>
from
<term>
context
</term>
, constrain the possible
<term>
word-senses
</term>
of
<term>
words with multiple meanings
</term>
(
<term>
ambiguity
</term>
) , fill in
<term>
missing words
</term>
(
<term>
elllpsis
</term>
) , and resolve
<term>
referents
</term>
(
<term>
anaphora
</term>
) .
|
#13074
These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possibleword-senses of words with multiple meanings (ambiguity), fill in missing words (elllpsis), and resolve referents (anaphora). |
other,4-5-P82-1035,bq |
This method of using
<term>
expectations
</term>
to aid the understanding of
<term>
scruffy texts
</term>
has been incorporated into a working
<term>
computer program
</term>
called
<term>
NOMAD
</term>
, which understands
<term>
scruffy texts
</term>
in the domain of Navy messages .
|
#13103
This method of usingexpectations to aid the understanding of scruffy texts has been incorporated into a working computer program called NOMAD, which understands scruffy texts in the domain of Navy messages. |
other,13-1-P82-1035,bq |
Most large
<term>
text-understanding systems
</term>
have been designed under the assumption that the input
<term>
text
</term>
will be in reasonably neat form , e.g. ,
<term>
newspaper stories
</term>
and other
<term>
edited texts
</term>
.
|
#12957
Most large text-understanding systems have been designed under the assumption that the inputtext will be in reasonably neat form, e.g., newspaper stories and other edited texts. |