Concordance

Query H91-1077 44 >
Random sample 44 (1,408.7 per million)

tech,3-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21941 A method ofsense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
tool,11-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21949 A method of sense resolution is proposed that is based onWordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
lr,15-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21953 A method of sense resolution is proposed that is based on WordNet, an on-linelexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
other,19-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21957 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporatessemantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
other,22-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21960 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
other,24-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21962 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy,antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
other,26-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21964 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy,hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses.
other,28-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21966 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy,meronymy, causal and troponymic entailment) as labeled pointers between word senses.
other,30-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21968 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy,causal and troponymic entailment) as labeled pointers between word senses.
other,39-1-H91-1077,ak	A method of <term> sense resolution </term> is proposed that is based on <term> WordNet </term> , an on-line <term> lexical database </term> that incorporates <term> semantic relations </term> ( <term> synonymy </term> , <term> antonymy </term> , <term> hyponymy </term> , <term> meronymy </term> , <term> causal and troponymic entailment </term> ) as labeled pointers between <term> word senses </term> .	#21977 A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers betweenword senses.
tool,1-2-H91-1077,ak	With <term> WordNet </term> , it is easy to retrieve sets of <term> semantically related words </term> , a facility that will be used for <term> sense resolution </term> during <term> text processing </term> , as follows .	#21981 WithWordNet, it is easy to retrieve sets of semantically related words, a facility that will be used for sense resolution during text processing, as follows.
other,10-2-H91-1077,ak	With <term> WordNet </term> , it is easy to retrieve sets of <term> semantically related words </term> , a facility that will be used for <term> sense resolution </term> during <term> text processing </term> , as follows .	#21990 With WordNet, it is easy to retrieve sets ofsemantically related words, a facility that will be used for sense resolution during text processing, as follows.
tech,21-2-H91-1077,ak	With <term> WordNet </term> , it is easy to retrieve sets of <term> semantically related words </term> , a facility that will be used for <term> sense resolution </term> during <term> text processing </term> , as follows .	#22001 With WordNet, it is easy to retrieve sets of semantically related words, a facility that will be used forsense resolution during text processing, as follows.
tech,24-2-H91-1077,ak	With <term> WordNet </term> , it is easy to retrieve sets of <term> semantically related words </term> , a facility that will be used for <term> sense resolution </term> during <term> text processing </term> , as follows .	#22004 With WordNet, it is easy to retrieve sets of semantically related words, a facility that will be used for sense resolution duringtext processing, as follows.
other,2-3-H91-1077,ak	When a <term> word </term> with multiple <term> senses </term> is encountered , one of two procedures will be followed .	#22012 When aword with multiple senses is encountered, one of two procedures will be followed.
other,5-3-H91-1077,ak	When a <term> word </term> with multiple <term> senses </term> is encountered , one of two procedures will be followed .	#22015 When a word with multiplesenses is encountered, one of two procedures will be followed.
other,5-4-H91-1077,ak	Either , ( 1 ) <term> words </term> related in <term> meaning </term> to the <term> alternative senses </term> of the <term> polysemous word </term> will be retrieved ; new strings will be derived by substituting these <term> related words </term> into the <term> context </term> of the <term> polysemous word </term> ; a <term> large textual corpus </term> will then be searched for these derived strings ; and that <term> sense </term> will be chosen that corresponds to the derived string that is found most often in the <term> corpus </term> .	#22032 Either, (1)words related in meaning to the alternative senses of the polysemous word will be retrieved; new strings will be derived by substituting these related words into the context of the polysemous word; a large textual corpus will then be searched for these derived strings; and that sense will be chosen that corresponds to the derived string that is found most often in the corpus.
other,8-4-H91-1077,ak	Either , ( 1 ) <term> words </term> related in <term> meaning </term> to the <term> alternative senses </term> of the <term> polysemous word </term> will be retrieved ; new strings will be derived by substituting these <term> related words </term> into the <term> context </term> of the <term> polysemous word </term> ; a <term> large textual corpus </term> will then be searched for these derived strings ; and that <term> sense </term> will be chosen that corresponds to the derived string that is found most often in the <term> corpus </term> .	#22035 Either, (1) words related inmeaning to the alternative senses of the polysemous word will be retrieved; new strings will be derived by substituting these related words into the context of the polysemous word; a large textual corpus will then be searched for these derived strings; and that sense will be chosen that corresponds to the derived string that is found most often in the corpus.
other,11-4-H91-1077,ak	Either , ( 1 ) <term> words </term> related in <term> meaning </term> to the <term> alternative senses </term> of the <term> polysemous word </term> will be retrieved ; new strings will be derived by substituting these <term> related words </term> into the <term> context </term> of the <term> polysemous word </term> ; a <term> large textual corpus </term> will then be searched for these derived strings ; and that <term> sense </term> will be chosen that corresponds to the derived string that is found most often in the <term> corpus </term> .	#22038 Either, (1) words related in meaning to thealternative senses of the polysemous word will be retrieved; new strings will be derived by substituting these related words into the context of the polysemous word; a large textual corpus will then be searched for these derived strings; and that sense will be chosen that corresponds to the derived string that is found most often in the corpus.
other,15-4-H91-1077,ak	Either , ( 1 ) <term> words </term> related in <term> meaning </term> to the <term> alternative senses </term> of the <term> polysemous word </term> will be retrieved ; new strings will be derived by substituting these <term> related words </term> into the <term> context </term> of the <term> polysemous word </term> ; a <term> large textual corpus </term> will then be searched for these derived strings ; and that <term> sense </term> will be chosen that corresponds to the derived string that is found most often in the <term> corpus </term> .	#22042 Either, (1) words related in meaning to the alternative senses of thepolysemous word will be retrieved; new strings will be derived by substituting these related words into the context of the polysemous word; a large textual corpus will then be searched for these derived strings; and that sense will be chosen that corresponds to the derived string that is found most often in the corpus.


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