| tech,21-4-C88-2162,ak | </term> [ Zernik88 ] , to facilitate <term> | language acquisition | </term> . From this , a <term> language learning | #18654 We introduced a new linguistic representation, the Dynamic Hierarchical Phrasal Lexicon (DHPL) [Zernik88], to facilitatelanguage acquisition. | |
| tech,4-2-C88-2162,ak | acquisition </term> . For one thing , <term> | learning methodology | </term> applicable in general domains does | #18601 For one thing,learning methodology applicable in general domains does not readily lend itself in the linguistic domain. | |
| other,3-7-C88-2162,ak | identified two tasks : First , how <term> | linguistic concepts | </term> are acquired from <term> training examples | #18691 First, howlinguistic concepts are acquired from training examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87]. | |
| 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 | #18724 Second, we show in this paper how alexical hierarchy is used in predicting new linguistic concepts. | |
| tech,7-3-C88-2162,ak | linguistic representation </term> used by <term> | language processing systems | </term> is not geared to <term> learning </term> | #18624 For another, linguistic representation used bylanguage processing systems is not geared to learning. | |
| model,4-5-C88-2162,ak | acquisition </term> . From this , a <term> | language learning model | </term> was implemented in the program <term> | #18661 From this, alanguage learning model was implemented in the program RINA, which enhances its own lexical hierarchy by processing examples in context. | |
| other,18-9-C88-2162,ak | presence of a lexical unknown , and a <term> | hypothesis | </term> can be produced for covering that | #18752 Thus, a program does not stall even in the presence of a lexical unknown, and ahypothesis can be produced for covering that lexical gap. | |
| model,14-7-C88-2162,ak | examples </term> and organized in a <term> | hierarchy | </term> ; this task was discussed in previous | #18702 First, how linguistic concepts are acquired from training examples and organized in ahierarchy; this task was discussed in previous papers [Zernik87]. | |
| other,24-5-C88-2162,ak | hierarchy </term> by processing examples in <term> | context | </term> . We identified two tasks : First | #18681 From this, a language learning model was implemented in the program RINA, which enhances its own lexical hierarchy by processing examples incontext. | |
| other,8-7-C88-2162,ak | linguistic concepts </term> are acquired from <term> | training examples | </term> and organized in a <term> hierarchy | #18696 First, how linguistic concepts are acquired fromtraining examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87]. | |
| tech,10-1-C88-2162,ak | far have not fared well in modeling <term> | language acquisition | </term> . For one thing , <term> learning methodology | #18594 Computer programs so far have not fared well in modelinglanguage acquisition. | |
| tech,14-3-C88-2162,ak | processing systems </term> is not geared to <term> | learning | </term> . We introduced a new <term> linguistic | #18631 For another, linguistic representation used by language processing systems is not geared tolearning. | |
| model,8-4-C88-2162,ak | linguistic representation </term> , the <term> | Dynamic Hierarchical Phrasal Lexicon ( DHPL ) | </term> [ Zernik88 ] , to facilitate <term> | #18641 We introduced a new linguistic representation, theDynamic Hierarchical Phrasal Lexicon ( DHPL ) [Zernik88], to facilitate language acquisition. | |
| other,25-9-C88-2162,ak | </term> can be produced for covering that <term> | lexical gap | </term> . Although every <term> natural language | #18759 Thus, a program does not stall even in the presence of a lexical unknown, and a hypothesis can be produced for covering thatlexical gap. | |
| tool,12-5-C88-2162,ak | </term> was implemented in the program <term> | RINA | </term> , which enhances its own <term> lexical | #18669 From this, a language learning model was implemented in the programRINA, which enhances its own lexical hierarchy by processing examples in context. | |
| model,18-5-C88-2162,ak | RINA </term> , which enhances its own <term> | lexical hierarchy | </term> by processing examples in <term> context | #18675 From 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 | #18731 Second, we show in this paper how a lexical hierarchy is used in predicting newlinguistic concepts. |
