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LitCovid-PAS-Enju

Id Subject Object Predicate Lexical cue
EnjuParser_T86 0-10 NN denotes Accounting
EnjuParser_T87 11-14 IN denotes for
EnjuParser_T88 15-18 DT denotes the
EnjuParser_T89 19-25 NN denotes impact
EnjuParser_T90 26-28 IN denotes of
EnjuParser_T91 29-32 DT denotes the
EnjuParser_T92 33-43 NNS denotes variations
EnjuParser_T93 44-46 IN denotes in
EnjuParser_T94 47-54 NN denotes disease
EnjuParser_T95 55-64 NN denotes reporting
EnjuParser_T96 65-69 NN denotes rate
EnjuParser_T97 69-70 -COMMA- denotes ,
EnjuParser_T98 71-73 PRP denotes we
EnjuParser_T99 74-82 VBD denotes modelled
EnjuParser_T100 83-86 DT denotes the
EnjuParser_T101 87-95 JJ denotes epidemic
EnjuParser_T102 96-101 NN denotes curve
EnjuParser_T103 102-104 IN denotes of
EnjuParser_T104 105-114 JJ denotes 2019-nCoV
EnjuParser_T105 115-120 NNS denotes cases
EnjuParser_T106 121-125 NN denotes time
EnjuParser_T107 126-132 NN denotes series
EnjuParser_T108 132-133 -COMMA- denotes ,
EnjuParser_T109 134-136 IN denotes in
EnjuParser_T110 137-145 NN denotes mainland
EnjuParser_T111 146-151 NNP denotes China
EnjuParser_T112 152-156 IN denotes from
EnjuParser_T113 157-164 NNP denotes January
EnjuParser_T114 165-167 CD denotes 10
EnjuParser_T115 168-170 TO denotes to
EnjuParser_T116 171-178 NNP denotes January
EnjuParser_T117 179-181 CD denotes 24
EnjuParser_T118 181-182 -COMMA- denotes ,
EnjuParser_T119 183-187 CD denotes 2020
EnjuParser_T120 187-188 -COMMA- denotes ,
EnjuParser_T121 189-196 IN denotes through
EnjuParser_T122 197-200 DT denotes the
EnjuParser_T123 201-212 JJ denotes exponential
EnjuParser_T124 213-219 NN denotes growth
EnjuParser_R82 EnjuParser_T86 EnjuParser_T87 arg1Of Accounting,for
EnjuParser_R83 EnjuParser_T89 EnjuParser_T87 arg2Of impact,for
EnjuParser_R84 EnjuParser_T89 EnjuParser_T88 arg1Of impact,the
EnjuParser_R85 EnjuParser_T89 EnjuParser_T90 arg1Of impact,of
EnjuParser_R86 EnjuParser_T92 EnjuParser_T90 arg2Of variations,of
EnjuParser_R87 EnjuParser_T92 EnjuParser_T91 arg1Of variations,the
EnjuParser_R88 EnjuParser_T92 EnjuParser_T93 arg1Of variations,in
EnjuParser_R89 EnjuParser_T96 EnjuParser_T93 arg2Of rate,in
EnjuParser_R90 EnjuParser_T96 EnjuParser_T94 arg1Of rate,disease
EnjuParser_R91 EnjuParser_T96 EnjuParser_T95 arg1Of rate,reporting
EnjuParser_R92 EnjuParser_T96 EnjuParser_T97 arg1Of rate,","
EnjuParser_R93 EnjuParser_T98 EnjuParser_T97 arg2Of we,","
EnjuParser_R94 EnjuParser_T86 EnjuParser_T99 arg1Of Accounting,modelled
EnjuParser_R95 EnjuParser_T102 EnjuParser_T99 arg2Of curve,modelled
EnjuParser_R96 EnjuParser_T102 EnjuParser_T100 arg1Of curve,the
EnjuParser_R97 EnjuParser_T102 EnjuParser_T101 arg1Of curve,epidemic
EnjuParser_R98 EnjuParser_T102 EnjuParser_T103 arg1Of curve,of
EnjuParser_R99 EnjuParser_T107 EnjuParser_T103 arg2Of series,of
EnjuParser_R100 EnjuParser_T107 EnjuParser_T104 arg1Of series,2019-nCoV
EnjuParser_R101 EnjuParser_T107 EnjuParser_T105 arg1Of series,cases
EnjuParser_R102 EnjuParser_T107 EnjuParser_T106 arg1Of series,time
EnjuParser_R103 EnjuParser_T99 EnjuParser_T108 arg1Of modelled,","
EnjuParser_R104 EnjuParser_T99 EnjuParser_T109 arg1Of modelled,in
EnjuParser_R105 EnjuParser_T111 EnjuParser_T109 arg2Of China,in
EnjuParser_R106 EnjuParser_T111 EnjuParser_T110 arg1Of China,mainland
EnjuParser_R107 EnjuParser_T99 EnjuParser_T112 arg1Of modelled,from
EnjuParser_R108 EnjuParser_T113 EnjuParser_T112 arg2Of January,from
EnjuParser_R109 EnjuParser_T113 EnjuParser_T114 arg1Of January,10
EnjuParser_R110 EnjuParser_T99 EnjuParser_T115 arg1Of modelled,to
EnjuParser_R111 EnjuParser_T118 EnjuParser_T115 arg2Of ",",to
EnjuParser_R112 EnjuParser_T116 EnjuParser_T117 arg1Of January,24
EnjuParser_R113 EnjuParser_T116 EnjuParser_T118 arg1Of January,","
EnjuParser_R114 EnjuParser_T119 EnjuParser_T118 arg2Of 2020,","
EnjuParser_R115 EnjuParser_T115 EnjuParser_T120 arg1Of to,","
EnjuParser_R116 EnjuParser_T121 EnjuParser_T120 arg2Of through,","
EnjuParser_R117 EnjuParser_T99 EnjuParser_T121 arg1Of modelled,through
EnjuParser_R118 EnjuParser_T124 EnjuParser_T121 arg2Of growth,through
EnjuParser_R119 EnjuParser_T124 EnjuParser_T122 arg1Of growth,the
EnjuParser_R120 EnjuParser_T124 EnjuParser_T123 arg1Of growth,exponential

LitCovid-OGER

Id Subject Object Predicate Lexical cue
T3 213-219 GO:0040007 denotes growth

LitCovid-OGER-BB

Id Subject Object Predicate Lexical cue
T8 105-114 SP_7 denotes 2019-nCoV

LitCovid-sentences-v1

Id Subject Object Predicate Lexical cue
TextSentencer_T7 0-220 Sentence denotes Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth.

LitCovid-TimeML

Id Subject Object Predicate Lexical cue
tok99 0-10 NNP denotes Accounting
tok100 11-14 IN denotes for
tok101 15-18 DT denotes the
tok102 19-25 NN denotes impact
tok103 26-28 IN denotes of
tok104 29-32 DT denotes the
tok105 33-43 NNS denotes variations
tok106 44-46 IN denotes in
tok107 47-54 NN denotes disease
tok108 55-64 VBG denotes reporting
tok109 65-69 NN denotes rate
tok110 69-70 , denotes ,
tok111 71-73 PRP denotes we
tok112 74-82 JJ denotes modelled
tok113 83-86 DT denotes the
tok114 87-95 NN denotes epidemic
tok115 96-101 NN denotes curve
tok116 102-104 IN denotes of
tok117 105-109 CD denotes 2019
tok118 109-110 : denotes -
tok119 110-114 NN denotes nCoV
tok120 115-120 NNS denotes cases
tok121 121-125 NN denotes time
tok122 126-132 NN denotes series
tok123 132-133 , denotes ,
tok124 134-136 IN denotes in
tok125 137-145 NN denotes mainland
tok126 146-151 NNP denotes China
tok127 152-156 IN denotes from
tok128 157-164 NNP denotes January
tok129 165-167 CD denotes 10
tok130 168-170 TO denotes to
tok131 171-178 NNP denotes January
tok132 179-181 CD denotes 24
tok133 181-182 , denotes ,
tok134 183-187 CD denotes 2020
tok135 187-188 , denotes ,
tok136 189-196 IN denotes through
tok137 197-200 DT denotes the
tok138 201-212 NN denotes exponential
tok139 213-219 NN denotes growth
tok140 219-220 . denotes .
lookup18 44-46 country_code denotes in
lookup19 105-109 year denotes 2019
lookup20 134-136 country_code denotes in
lookup21 146-151 location denotes China
lookup22 157-164 date denotes January
lookup23 168-170 country_code denotes to
lookup24 171-178 date denotes January
lookup25 183-187 year denotes 2020