| tech,2-1-C88-2166,ak | lexical gap </term> . Although every <term> | natural language system | </term> needs a <term> computational lexicon | #18764 Although everynatural language system needs a computational lexicon, each system puts different amounts and types of information into its lexicon according to its individual needs. | |
| lr,7-1-C88-2166,ak | natural language system </term> needs a <term> | computational lexicon | </term> , each <term> system </term> puts different | #18769 Although every natural language system needs acomputational lexicon, each system puts different amounts and types of information into its lexicon according to its individual needs. | |
| tech,11-1-C88-2166,ak | computational lexicon </term> , each <term> | system | </term> puts different amounts and types | #18773 Although every natural language system needs a computational lexicon, eachsystem puts different amounts and types of information into its lexicon according to its individual needs. | |
| other,18-1-C88-2166,ak | puts different amounts and types of <term> | information | </term> into its <term> lexicon </term> according | #18780 Although every natural language system needs a computational lexicon, each system puts different amounts and types ofinformation into its lexicon according to its individual needs. | |
| lr,21-1-C88-2166,ak | of <term> information </term> into its <term> | lexicon | </term> according to its individual needs | #18783 Although every natural language system needs a computational lexicon, each system puts different amounts and types of information into itslexicon according to its individual needs. | |
| other,5-2-C88-2166,ak | individual needs . However , some of the <term> | information | </term> needed across <term> systems </term> | #18795 However, some of theinformation needed across systems is shared or identical information. | |
| tech,8-2-C88-2166,ak | <term> information </term> needed across <term> | systems | </term> is shared or identical <term> information | #18798 However, some of the information needed acrosssystems is shared or identical information. | |
| other,13-2-C88-2166,ak | systems </term> is shared or identical <term> | information | </term> . This paper presents our experience | #18803 However, some of the information needed across systems is shared or identicalinformation. | |
| tool,9-3-C88-2166,ak | experience in planning and building <term> | COMPLEX | </term> , a <term> computational lexicon </term> | #18814 This paper presents our experience in planning and buildingCOMPLEX, a computational lexicon designed to be a repository of shared lexical information for use by Natural Language Processing (NLP) systems. | |
| lr,12-3-C88-2166,ak | and building <term> COMPLEX </term> , a <term> | computational lexicon | </term> designed to be a <term> repository </term> | #18817 This paper presents our experience in planning and building COMPLEX, acomputational lexicon designed to be a repository of shared lexical information for use by Natural Language Processing (NLP) systems. | |
| lr,18-3-C88-2166,ak | computational lexicon </term> designed to be a <term> | repository | </term> of shared <term> lexical information | #18823 This paper presents our experience in planning and building COMPLEX, a computational lexicon designed to be arepository of shared lexical information for use by Natural Language Processing (NLP) systems. | |
| other,21-3-C88-2166,ak | a <term> repository </term> of shared <term> | lexical information | </term> for use by <term> Natural Language | #18826 This paper presents our experience in planning and building COMPLEX, a computational lexicon designed to be a repository of sharedlexical information for use by Natural Language Processing (NLP) systems. | |
| tech,26-3-C88-2166,ak | lexical information </term> for use by <term> | Natural Language Processing ( NLP ) systems | </term> . We have drawn primarily on explicit | #18831 This paper presents our experience in planning and building COMPLEX, a computational lexicon designed to be a repository of shared lexical information for use byNatural Language Processing ( NLP ) systems. | |
| other,8-4-C88-2166,ak | primarily on explicit and implicit <term> | information | </term> from <term> machine-readable dictionaries | #18847 We have drawn primarily on explicit and implicitinformation from machine-readable dictionaries (MRD's) to create a broad coverage lexicon. | |
| lr,10-4-C88-2166,ak | implicit <term> information </term> from <term> | machine-readable dictionaries ( MRD 's ) | </term> to create a <term> broad coverage lexicon | #18849 We have drawn primarily on explicit and implicit information frommachine-readable dictionaries ( MRD 's ) to create a broad coverage lexicon. | |
| lr,19-4-C88-2166,ak | dictionaries ( MRD 's ) </term> to create a <term> | broad coverage lexicon | </term> . For <term> intelligent interactive | #18858 We have drawn primarily on explicit and implicit information from machine-readable dictionaries (MRD's) to create abroad coverage lexicon. |
