| other,50-5-H91-1077,ak | from those <term> words </term> to the <term> | alternative senses | </term> of the <term> polysemous word </term> | #22150 Or, (2) the context of the polysemous word will be used as a key to search a large corpus; all words found to occur in that context will be noted; WordNet will then be used to estimate the semantic distance from those words to thealternative senses of the polysemous word; and that sense will be chosen that is closest in meaning to other words occurring in the same context. | |
| tech,21-2-H91-1077,ak | , a facility that will be used for <term> | sense resolution | </term> during <term> text processing </term> | #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. | |
| lr,15-1-H91-1077,ak | on <term> WordNet </term> , an on-line <term> | lexical database | </term> that incorporates <term> semantic relations | #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,15-4-H91-1077,ak | <term> alternative senses </term> of the <term> | polysemous word | </term> will be retrieved ; new strings will | #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. | |
| tech,24-2-H91-1077,ak | <term> sense resolution </term> during <term> | text processing | </term> , as follows . When a <term> word </term> | #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,28-1-H91-1077,ak | antonymy </term> , <term> hyponymy </term> , <term> | meronymy | </term> , <term> causal and troponymic entailment | #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,26-1-H91-1077,ak | synonymy </term> , <term> antonymy </term> , <term> | hyponymy | </term> , <term> meronymy </term> , <term> causal | #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,54-4-H91-1077,ak | for these derived strings ; and that <term> | sense | </term> will be chosen that corresponds to | #22081 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 thatsense will be chosen that corresponds to the derived string that is found most often in the corpus. | |
| tool,11-1-H91-1077,ak | </term> is proposed that is based on <term> | WordNet | </term> , an on-line <term> lexical database | #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,20-5-H91-1077,ak | used as a <term> key </term> to search a <term> | large corpus | </term> ; all <term> words </term> found to occur | #22120 Or, (2) the context of the polysemous word will be used as a key to search alarge corpus; all words found to occur in that context will be noted; WordNet will then be used to estimate the semantic distance from those words to the alternative senses of the polysemous word; and that sense will be chosen that is closest in meaning to other words occurring in the same context. | |
| other,8-4-H91-1077,ak | ( 1 ) <term> words </term> related in <term> | meaning | </term> to the <term> alternative senses </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,5-3-H91-1077,ak | When a <term> word </term> with multiple <term> | senses | </term> is encountered , one of two procedures | #22015 When a word with multiplesenses is encountered, one of two procedures will be followed. | |
| tech,12-6-H91-1077,ak | practical applications to problems of <term> | information retrieval | </term> , <term> mechanical translation </term> | #22189 If successful, this procedure could have practical applications to problems ofinformation retrieval, mechanical translation, intelligent tutoring systems, and elsewhere. | |
| other,67-5-H91-1077,ak | </term> will be chosen that is closest in <term> | meaning | </term> to other <term> words </term> occurring | #22167 Or, (2) the context of the polysemous word will be used as a key to search a large corpus; all words found to occur in that context will be noted; WordNet will then be used to estimate the semantic distance from those words to the alternative senses of the polysemous word; and that sense will be chosen that is closest inmeaning to other words occurring in the same context. | |
| other,24-5-H91-1077,ak | search a <term> large corpus </term> ; all <term> | words | </term> found to occur in that <term> context | #22124 Or, (2) the context of the polysemous word will be used as a key to search a large corpus; allwords found to occur in that context will be noted; WordNet will then be used to estimate the semantic distance from those words to the alternative senses of the polysemous word; and that sense will be chosen that is closest in meaning to other words occurring in the same context. | |
| other,59-5-H91-1077,ak | <term> polysemous word </term> ; and that <term> | sense | </term> will be chosen that is closest in | #22159 Or, (2) the context of the polysemous word will be used as a key to search a large corpus; all words found to occur in that context will be noted; WordNet will then be used to estimate the semantic distance from those words to the alternative senses of the polysemous word; and thatsense will be chosen that is closest in meaning to other words occurring in the same context. | |
| lr,71-4-H91-1077,ak | string that is found most often in the <term> | corpus | </term> . Or , ( 2 ) the <term> context </term> | #22098 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 thecorpus. | |
| other,22-1-H91-1077,ak | incorporates <term> semantic relations </term> ( <term> | synonymy | </term> , <term> antonymy </term> , <term> hyponymy | #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 | relations </term> ( <term> synonymy </term> , <term> | antonymy | </term> , <term> hyponymy </term> , <term> meronymy | #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. | |
| tech,15-6-H91-1077,ak | <term> information retrieval </term> , <term> | mechanical translation | </term> , <term> intelligent tutoring systems | #22192 If successful, this procedure could have practical applications to problems of information retrieval,mechanical translation, intelligent tutoring systems, and elsewhere. |
