PMC:7371427 / 64697-65489 JSONTXT

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T660","span":{"begin":187,"end":191},"obj":"Body_part"},{"id":"T661","span":{"begin":322,"end":328},"obj":"Body_part"},{"id":"T662","span":{"begin":573,"end":579},"obj":"Body_part"}],"attributes":[{"id":"A660","pred":"fma_id","subj":"T660","obj":"http://purl.org/sig/ont/fma/fma74402"},{"id":"A661","pred":"fma_id","subj":"T661","obj":"http://purl.org/sig/ont/fma/fma7203"},{"id":"A662","pred":"fma_id","subj":"T662","obj":"http://purl.org/sig/ont/fma/fma7203"}],"text":"One demonstration of the use of the logical query system is to disambiguate a token by conjoining it with a disambiguating token. An example is clearer: the token ‘egfr’ can refer to the gene entity epidermal growth factor receptor, but also the test measure entity estimated glomerular filtration rate. A query ‘egfr AND kidney’ should return results related to the latter meaning, while ‘egfr AND lung_cancer’ the former. In particular, an unambiguous referent to the right entity should be highly related to the query. So example known pairs in this data are (‘egfr AND kidney’, ‘estimated_glomerular_filtration_rate’) and (‘egfr AND lung_cancer’, ‘epidermal_growth_factor_receptor’). We used an internal set of ~200–300 such (‘A AND B’, ‘C’) pairs (originally built up for other reasons)."}

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T283","span":{"begin":322,"end":328},"obj":"Body_part"},{"id":"T284","span":{"begin":573,"end":579},"obj":"Body_part"}],"attributes":[{"id":"A283","pred":"uberon_id","subj":"T283","obj":"http://purl.obolibrary.org/obo/UBERON_0002113"},{"id":"A284","pred":"uberon_id","subj":"T284","obj":"http://purl.obolibrary.org/obo/UBERON_0002113"}],"text":"One demonstration of the use of the logical query system is to disambiguate a token by conjoining it with a disambiguating token. An example is clearer: the token ‘egfr’ can refer to the gene entity epidermal growth factor receptor, but also the test measure entity estimated glomerular filtration rate. A query ‘egfr AND kidney’ should return results related to the latter meaning, while ‘egfr AND lung_cancer’ the former. In particular, an unambiguous referent to the right entity should be highly related to the query. So example known pairs in this data are (‘egfr AND kidney’, ‘estimated_glomerular_filtration_rate’) and (‘egfr AND lung_cancer’, ‘epidermal_growth_factor_receptor’). We used an internal set of ~200–300 such (‘A AND B’, ‘C’) pairs (originally built up for other reasons)."}

{"project":"LitCovid-PubTator","denotations":[{"id":"192","span":{"begin":404,"end":410},"obj":"Disease"},{"id":"193","span":{"begin":642,"end":648},"obj":"Disease"}],"attributes":[{"id":"A192","pred":"tao:has_database_id","subj":"192","obj":"MESH:D009369"},{"id":"A193","pred":"tao:has_database_id","subj":"193","obj":"MESH:D009369"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"One demonstration of the use of the logical query system is to disambiguate a token by conjoining it with a disambiguating token. An example is clearer: the token ‘egfr’ can refer to the gene entity epidermal growth factor receptor, but also the test measure entity estimated glomerular filtration rate. A query ‘egfr AND kidney’ should return results related to the latter meaning, while ‘egfr AND lung_cancer’ the former. In particular, an unambiguous referent to the right entity should be highly related to the query. So example known pairs in this data are (‘egfr AND kidney’, ‘estimated_glomerular_filtration_rate’) and (‘egfr AND lung_cancer’, ‘epidermal_growth_factor_receptor’). We used an internal set of ~200–300 such (‘A AND B’, ‘C’) pairs (originally built up for other reasons)."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T995","span":{"begin":76,"end":77},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T996","span":{"begin":106,"end":107},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T997","span":{"begin":187,"end":191},"obj":"http://purl.obolibrary.org/obo/OGG_0000000002"},{"id":"T998","span":{"begin":246,"end":250},"obj":"http://purl.obolibrary.org/obo/UBERON_0000473"},{"id":"T999","span":{"begin":304,"end":305},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T1000","span":{"begin":322,"end":328},"obj":"http://purl.obolibrary.org/obo/UBERON_0002113"},{"id":"T1001","span":{"begin":322,"end":328},"obj":"http://www.ebi.ac.uk/efo/EFO_0000927"},{"id":"T1002","span":{"begin":322,"end":328},"obj":"http://www.ebi.ac.uk/efo/EFO_0000929"},{"id":"T1003","span":{"begin":573,"end":579},"obj":"http://purl.obolibrary.org/obo/UBERON_0002113"},{"id":"T1004","span":{"begin":573,"end":579},"obj":"http://www.ebi.ac.uk/efo/EFO_0000927"},{"id":"T1005","span":{"begin":573,"end":579},"obj":"http://www.ebi.ac.uk/efo/EFO_0000929"},{"id":"T1006","span":{"begin":731,"end":732},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T1007","span":{"begin":737,"end":738},"obj":"http://purl.obolibrary.org/obo/CLO_0001021"}],"text":"One demonstration of the use of the logical query system is to disambiguate a token by conjoining it with a disambiguating token. An example is clearer: the token ‘egfr’ can refer to the gene entity epidermal growth factor receptor, but also the test measure entity estimated glomerular filtration rate. A query ‘egfr AND kidney’ should return results related to the latter meaning, while ‘egfr AND lung_cancer’ the former. In particular, an unambiguous referent to the right entity should be highly related to the query. So example known pairs in this data are (‘egfr AND kidney’, ‘estimated_glomerular_filtration_rate’) and (‘egfr AND lung_cancer’, ‘epidermal_growth_factor_receptor’). We used an internal set of ~200–300 such (‘A AND B’, ‘C’) pairs (originally built up for other reasons)."}

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T66","span":{"begin":209,"end":215},"obj":"http://purl.obolibrary.org/obo/GO_0040007"},{"id":"T67","span":{"begin":276,"end":297},"obj":"http://purl.obolibrary.org/obo/GO_0003094"}],"text":"One demonstration of the use of the logical query system is to disambiguate a token by conjoining it with a disambiguating token. An example is clearer: the token ‘egfr’ can refer to the gene entity epidermal growth factor receptor, but also the test measure entity estimated glomerular filtration rate. A query ‘egfr AND kidney’ should return results related to the latter meaning, while ‘egfr AND lung_cancer’ the former. In particular, an unambiguous referent to the right entity should be highly related to the query. So example known pairs in this data are (‘egfr AND kidney’, ‘estimated_glomerular_filtration_rate’) and (‘egfr AND lung_cancer’, ‘epidermal_growth_factor_receptor’). We used an internal set of ~200–300 such (‘A AND B’, ‘C’) pairs (originally built up for other reasons)."}

{"project":"LitCovid-sentences","denotations":[{"id":"T375","span":{"begin":0,"end":129},"obj":"Sentence"},{"id":"T376","span":{"begin":130,"end":303},"obj":"Sentence"},{"id":"T377","span":{"begin":304,"end":423},"obj":"Sentence"},{"id":"T378","span":{"begin":424,"end":521},"obj":"Sentence"},{"id":"T379","span":{"begin":522,"end":687},"obj":"Sentence"},{"id":"T380","span":{"begin":688,"end":792},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"One demonstration of the use of the logical query system is to disambiguate a token by conjoining it with a disambiguating token. An example is clearer: the token ‘egfr’ can refer to the gene entity epidermal growth factor receptor, but also the test measure entity estimated glomerular filtration rate. A query ‘egfr AND kidney’ should return results related to the latter meaning, while ‘egfr AND lung_cancer’ the former. In particular, an unambiguous referent to the right entity should be highly related to the query. So example known pairs in this data are (‘egfr AND kidney’, ‘estimated_glomerular_filtration_rate’) and (‘egfr AND lung_cancer’, ‘epidermal_growth_factor_receptor’). We used an internal set of ~200–300 such (‘A AND B’, ‘C’) pairs (originally built up for other reasons)."}