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PMC:7371427 / 3966-4878 JSONTXT

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LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T12 194-200 Body_part denotes corpus http://purl.obolibrary.org/obo/UBERON_3000645

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T49 36-39 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T50 232-235 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T51 398-399 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T52 516-519 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T53 757-764 http://purl.obolibrary.org/obo/SO_0000418 denotes signals

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T9 27-35 http://purl.obolibrary.org/obo/GO_0007612 denotes learning

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T24 0-383 Sentence denotes While unsupervised machine learning has been advanced to study the semantic relationships between word embeddings (Mikolov et al., 2013a; LeCun et al., 2015) and applied to the material science corpus (Tshitoyan et al., 2019), this has not been scaled-up to extract the ‘global context’ of conceptual associations from the entirety of publicly available unstructured biomedical text.
T25 384-637 Sentence denotes Additionally, a principled way of accounting for the distances between phrases captured from the ever-growing scientific literature has not been comprehensively researched to quantify the strength of ‘local context’ between pairs of biological concepts.
T26 638-912 Sentence denotes Given the propensity for irreproducible or erroneous scientific research (Nature Editorial, 2016), any local or global signals extracted from this unstructured knowledge need to be seamlessly triangulated with deep biological insights emergent from various omics data silos.

MyTest

Id Subject Object Predicate Lexical cue
32463365-26017442-27519071 152-156 26017442 denotes 2015
32463365-31270483-27519072 220-224 31270483 denotes 2019
32463365-27225078-27519073 730-734 27225078 denotes 2016

2_test

Id Subject Object Predicate Lexical cue
32463365-26017442-27519071 152-156 26017442 denotes 2015
32463365-31270483-27519072 220-224 31270483 denotes 2019
32463365-27225078-27519073 730-734 27225078 denotes 2016