hierarchy
</term>
by processing examples in
<term>
context
</term>
. We identified two tasks : First
#18681From this, a language learning model was implemented in the program RINA, which enhances its own lexical hierarchy by processing examples incontext.
model,8-4-C88-2162,ak
linguistic representation
</term>
, the
<term>
Dynamic Hierarchical Phrasal Lexicon ( DHPL )
</term>
[ Zernik88 ] , to facilitate
<term>
#18641We introduced a new linguistic representation, theDynamic Hierarchical Phrasal Lexicon ( DHPL ) [Zernik88], to facilitate language acquisition.
model,14-7-C88-2162,ak
examples
</term>
and organized in a
<term>
hierarchy
</term>
; this task was discussed in previous
#18702First, how linguistic concepts are acquired from training examples and organized in ahierarchy; this task was discussed in previous papers [Zernik87].
other,18-9-C88-2162,ak
presence of a lexical unknown , and a
<term>
hypothesis
</term>
can be produced for covering that
#18752Thus, a program does not stall even in the presence of a lexical unknown, and ahypothesis can be produced for covering that lexical gap.
tech,10-1-C88-2162,ak
far have not fared well in modeling
<term>
language acquisition
</term>
. For one thing ,
<term>
learning methodology
#18594Computer programs so far have not fared well in modelinglanguage acquisition.
tech,21-4-C88-2162,ak
</term>
[ Zernik88 ] , to facilitate
<term>
language acquisition
</term>
. From this , a
<term>
language learning
#18654We introduced a new linguistic representation, the Dynamic Hierarchical Phrasal Lexicon (DHPL) [Zernik88], to facilitatelanguage acquisition.
model,4-5-C88-2162,ak
acquisition
</term>
. From this , a
<term>
language learning model
</term>
was implemented in the program
<term>
#18661From this, alanguage learning model was implemented in the program RINA, which enhances its own lexical hierarchy by processing examples in context.
tech,7-3-C88-2162,ak
linguistic representation
</term>
used by
<term>
language processing systems
</term>
is not geared to
<term>
learning
</term>
#18624For another, linguistic representation used bylanguage processing systems is not geared to learning.
tech,14-3-C88-2162,ak
processing systems
</term>
is not geared to
<term>
learning
</term>
. We introduced a new
<term>
linguistic
#18631For another, linguistic representation used by language processing systems is not geared tolearning.
tech,4-2-C88-2162,ak
acquisition
</term>
. For one thing ,
<term>
learning methodology
</term>
applicable in general domains does
#18601For one thing,learning methodology applicable in general domains does not readily lend itself in the linguistic domain.
other,25-9-C88-2162,ak
</term>
can be produced for covering that
<term>
lexical gap
</term>
. Although every
<term>
natural language
#18759Thus, a program does not stall even in the presence of a lexical unknown, and a hypothesis can be produced for covering thatlexical gap.
model,9-8-C88-2162,ak
Second , we show in this paper how a
<term>
lexical hierarchy
</term>
is used in predicting new
<term>
linguistic
#18724Second, we show in this paper how alexical hierarchy is used in predicting new linguistic concepts.
model,18-5-C88-2162,ak
RINA
</term>
, which enhances its own
<term>
lexical hierarchy
</term>
by processing examples in
<term>
context
#18675From this, a language learning model was implemented in the program RINA, which enhances its ownlexical hierarchy by processing examples in context.
other,16-8-C88-2162,ak
hierarchy
</term>
is used in predicting new
<term>
linguistic concepts
</term>
. Thus , a program does not stall
#18731Second, we show in this paper how a lexical hierarchy is used in predicting newlinguistic concepts.
other,3-7-C88-2162,ak
identified two tasks : First , how
<term>
linguistic concepts
</term>
are acquired from
<term>
training examples
#18691First, howlinguistic concepts are acquired from training examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87].
model,3-3-C88-2162,ak
linguistic domain . For another ,
<term>
linguistic representation
</term>
used by
<term>
language processing
#18620For another,linguistic representation used by language processing systems is not geared to learning.
model,4-4-C88-2162,ak
learning
</term>
. We introduced a new
<term>
linguistic representation
</term>
, the
<term>
Dynamic Hierarchical Phrasal
#18637We introduced a newlinguistic representation, the Dynamic Hierarchical Phrasal Lexicon (DHPL) [Zernik88], to facilitate language acquisition.
tool,12-5-C88-2162,ak
</term>
was implemented in the program
<term>
RINA
</term>
, which enhances its own
<term>
lexical
#18669From this, a language learning model was implemented in the programRINA, which enhances its own lexical hierarchy by processing examples in context.
other,8-7-C88-2162,ak
linguistic concepts
</term>
are acquired from
<term>
training examples
</term>
and organized in a
<term>
hierarchy
#18696First, how linguistic concepts are acquired fromtraining examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87].