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PubMed:32087820 / 576-747 JSONTXT

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LitCovid-PAS-Enju

Id Subject Object Predicate Lexical cue
EnjuParser_T89 0-2 PRP denotes We
EnjuParser_T90 3-7 VBD denotes used
EnjuParser_T91 8-12 NNS denotes data
EnjuParser_T92 13-15 IN denotes on
EnjuParser_T93 16-19 DT denotes the
EnjuParser_T94 20-26 NN denotes volume
EnjuParser_T95 27-29 IN denotes of
EnjuParser_T96 30-33 NN denotes air
EnjuParser_T97 34-40 NN denotes travel
EnjuParser_T98 41-50 VBG denotes departing
EnjuParser_T99 51-55 IN denotes from
EnjuParser_T100 56-64 NNS denotes airports
EnjuParser_T101 65-67 IN denotes in
EnjuParser_T102 68-71 DT denotes the
EnjuParser_T103 72-80 JJ denotes infected
EnjuParser_T104 81-90 NNS denotes provinces
EnjuParser_T105 91-93 IN denotes in
EnjuParser_T106 94-99 NNP denotes China
EnjuParser_T107 100-103 CC denotes and
EnjuParser_T108 104-112 VBN denotes directed
EnjuParser_T109 113-115 TO denotes to
EnjuParser_T110 116-122 NNP denotes Africa
EnjuParser_T111 123-125 TO denotes to
EnjuParser_T112 126-134 VB denotes estimate
EnjuParser_T113 135-138 DT denotes the
EnjuParser_T114 139-143 NN denotes risk
EnjuParser_T115 144-146 IN denotes of
EnjuParser_T116 147-158 NN denotes importation
EnjuParser_T117 159-162 IN denotes per
EnjuParser_T118 163-170 NN denotes country
EnjuParser_R84 EnjuParser_T89 EnjuParser_T90 arg1Of We,used
EnjuParser_R85 EnjuParser_T91 EnjuParser_T90 arg2Of data,used
EnjuParser_R86 EnjuParser_T91 EnjuParser_T92 arg1Of data,on
EnjuParser_R87 EnjuParser_T94 EnjuParser_T92 arg2Of volume,on
EnjuParser_R88 EnjuParser_T94 EnjuParser_T93 arg1Of volume,the
EnjuParser_R89 EnjuParser_T94 EnjuParser_T95 arg1Of volume,of
EnjuParser_R90 EnjuParser_T97 EnjuParser_T95 arg2Of travel,of
EnjuParser_R91 EnjuParser_T97 EnjuParser_T96 arg1Of travel,air
EnjuParser_R92 EnjuParser_T97 EnjuParser_T98 arg1Of travel,departing
EnjuParser_R93 EnjuParser_T98 EnjuParser_T99 arg1Of departing,from
EnjuParser_R94 EnjuParser_T100 EnjuParser_T99 arg2Of airports,from
EnjuParser_R95 EnjuParser_T100 EnjuParser_T101 arg1Of airports,in
EnjuParser_R96 EnjuParser_T104 EnjuParser_T101 arg2Of provinces,in
EnjuParser_R97 EnjuParser_T104 EnjuParser_T102 arg1Of provinces,the
EnjuParser_R98 EnjuParser_T104 EnjuParser_T103 arg1Of provinces,infected
EnjuParser_R99 EnjuParser_T104 EnjuParser_T105 arg1Of provinces,in
EnjuParser_R100 EnjuParser_T106 EnjuParser_T105 arg2Of China,in
EnjuParser_R101 EnjuParser_T91 EnjuParser_T107 arg1Of data,and
EnjuParser_R102 EnjuParser_T91 EnjuParser_T108 arg2Of data,directed
EnjuParser_R103 EnjuParser_T108 EnjuParser_T109 arg1Of directed,to
EnjuParser_R104 EnjuParser_T110 EnjuParser_T109 arg2Of Africa,to
EnjuParser_R105 EnjuParser_T112 EnjuParser_T111 arg1Of estimate,to
EnjuParser_R106 EnjuParser_T108 EnjuParser_T111 modOf directed,to
EnjuParser_R107 EnjuParser_T114 EnjuParser_T112 arg2Of risk,estimate
EnjuParser_R108 EnjuParser_T114 EnjuParser_T113 arg1Of risk,the
EnjuParser_R109 EnjuParser_T114 EnjuParser_T115 arg1Of risk,of
EnjuParser_R110 EnjuParser_T116 EnjuParser_T115 arg2Of importation,of
EnjuParser_R111 EnjuParser_T114 EnjuParser_T117 arg1Of risk,per
EnjuParser_R112 EnjuParser_T118 EnjuParser_T117 arg2Of country,per

LitCovid-OGER

Id Subject Object Predicate Lexical cue
T2 30-33 PR:000022063 denotes air

LitCovid-sentences-v1

Id Subject Object Predicate Lexical cue
TextSentencer_T9 0-171 Sentence denotes We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country.

LitCovid-TimeML

Id Subject Object Predicate Lexical cue
tok99 0-2 PRP denotes We
tok100 3-7 VBD denotes used
tok101 8-12 NNS denotes data
tok102 13-15 IN denotes on
tok103 16-19 DT denotes the
tok104 20-26 NN denotes volume
tok105 27-29 IN denotes of
tok106 30-33 NN denotes air
tok107 34-40 NN denotes travel
tok108 41-50 VBG denotes departing
tok109 51-55 IN denotes from
tok110 56-64 NNS denotes airports
tok111 65-67 IN denotes in
tok112 68-71 DT denotes the
tok113 72-80 JJ denotes infected
tok114 81-90 NNS denotes provinces
tok115 91-93 IN denotes in
tok116 94-99 NNP denotes China
tok117 100-103 CC denotes and
tok118 104-112 VBN denotes directed
tok119 113-115 TO denotes to
tok120 116-122 NNP denotes Africa
tok121 123-125 TO denotes to
tok122 126-134 VB denotes estimate
tok123 135-138 DT denotes the
tok124 139-143 NN denotes risk
tok125 144-146 IN denotes of
tok126 147-158 NN denotes importation
tok127 159-162 IN denotes per
tok128 163-170 NN denotes country
tok129 170-171 . denotes .
lookup12 0-2 stop denotes We
lookup13 65-67 country_code denotes in
lookup14 91-93 country_code denotes in
lookup15 94-99 location denotes China
lookup16 113-115 country_code denotes to
lookup17 116-122 location denotes Africa
lookup18 123-125 country_code denotes to
lookup19 159-162 person_first denotes per
event1 104-112 OCCURRENCE denotes directed
event10 126-134 OCCURRENCE denotes estimate
event18 41-50 OCCURRENCE denotes departing
event23 3-7 OCCURRENCE denotes used