Dataset Viewer
Auto-converted to Parquet Duplicate
id
string
image
image
query
dict
answers
list
words
list
bounding_boxes
list
answer
dict
train_337
{ "en": "what is the date mentioned in this letter?" }
[ "1/8/93" ]
[ "Confidential", "..", "..", "RJRT", "PR", "APPROVAL", "DATE", ":", "1/8/13", "Ru", "alAs", "PROPOSED", "RELEASE", "DATE:", "for", "response", "FOR", "RELEASE", "TO:", "CONTACT:", "P.", "CARTER", "ROUTE", "TO", "Initials", "pate", "Peggy", "Carter", "Ac", "Ma...
[ [ 584, 30, 994, 131 ], [ 1080, 32, 1099, 55 ], [ 1102, 31, 1124, 54 ], [ 699, 203, 779, 234 ], [ 793, 204, 832, 234 ], [ 848, 204, 995, 237 ], [ 259, 295, 331, 323 ], [ 335...
{ "match_score": 0, "matched_text": "", "start": -1, "text": "1/8/93" }
train_338
{ "en": "what is the contact person name mentioned in letter?" }
[ "P. Carter", "p. carter" ]
[ "Confidential", "..", "..", "RJRT", "PR", "APPROVAL", "DATE", ":", "1/8/13", "Ru", "alAs", "PROPOSED", "RELEASE", "DATE:", "for", "response", "FOR", "RELEASE", "TO:", "CONTACT:", "P.", "CARTER", "ROUTE", "TO", "Initials", "pate", "Peggy", "Carter", "Ac", "Ma...
[ [ 584, 30, 994, 131 ], [ 1080, 32, 1099, 55 ], [ 1102, 31, 1124, 54 ], [ 699, 203, 779, 234 ], [ 793, 204, 832, 234 ], [ 848, 204, 995, 237 ], [ 259, 295, 331, 323 ], [ 335...
{ "match_score": 0.6666666865348816, "matched_text": "CARTER", "start": 21, "text": "P. Carter" }
train_339
{ "en": "Which corporation's letterhead is this?" }
[ "Brown & Williamson Tobacco Corporation" ]
[ "B&W", "BROWN", "&", "WILLIAMSON", "TOBACCO", "CORPORATION", "RESEARCH", "&", "DEVELOPMENT", ".", ".", ".", ".", "INTERNAL", "CORRESPONDENCE", "TO:", "R.", "H.", "Honeycutt", "CC:", "T.F.", "Riehl", "FROM:", "C.", "J.", "Cook", "DATE:", "May", "8.", "1995", ...
[ [ 733, 193, 791, 219 ], [ 477, 251, 567, 276 ], [ 572, 251, 592, 275 ], [ 599, 251, 756, 274 ], [ 765, 250, 881, 273 ], [ 888, 248, 1065, 274 ], [ 598, 279, 724, 303 ], [ 7...
{ "match_score": 0.28947368264198303, "matched_text": "CORPORATION", "start": 5, "text": "Brown & Williamson Tobacco Corporation" }
train_340
{ "en": "Who is in cc in this letter?" }
[ "T.F. Riehl" ]
[ "B&W", "BROWN", "&", "WILLIAMSON", "TOBACCO", "CORPORATION", "RESEARCH", "&", "DEVELOPMENT", ".", ".", ".", ".", "INTERNAL", "CORRESPONDENCE", "TO:", "R.", "H.", "Honeycutt", "CC:", "T.F.", "Riehl", "FROM:", "C.", "J.", "Cook", "DATE:", "May", "8.", "1995", ...
[ [ 733, 193, 791, 219 ], [ 477, 251, 567, 276 ], [ 572, 251, 592, 275 ], [ 599, 251, 756, 274 ], [ 765, 250, 881, 273 ], [ 888, 248, 1065, 274 ], [ 598, 279, 724, 303 ], [ 7...
{ "match_score": 0.5, "matched_text": "Riehl", "start": 21, "text": "T.F. Riehl" }
train_341
{ "en": "what is the subject of this letter?" }
[ "Review of existing Brainstorming Ideas/483" ]
[ "B&W", "BROWN", "&", "WILLIAMSON", "TOBACCO", "CORPORATION", "RESEARCH", "&", "DEVELOPMENT", ".", ".", ".", ".", "INTERNAL", "CORRESPONDENCE", "TO:", "R.", "H.", "Honeycutt", "CC:", "T.F.", "Riehl", "FROM:", "C.", "J.", "Cook", "DATE:", "May", "8.", "1995", ...
[ [ 733, 193, 791, 219 ], [ 477, 251, 567, 276 ], [ 572, 251, 592, 275 ], [ 599, 251, 756, 274 ], [ 765, 250, 881, 273 ], [ 888, 248, 1065, 274 ], [ 598, 279, 724, 303 ], [ 7...
{ "match_score": 0.3095238208770752, "matched_text": "Brainstorming", "start": 34, "text": "Review of existing Brainstorming Ideas/483" }
train_343
{ "en": "What is the number at the bottom of the page, in bold?" }
[ "499150498" ]
[ "B&W", "BROWN", "&", "WILLIAMSON", "TOBACCO", "CORPORATION", "RESEARCH", "&", "DEVELOPMENT", ".", ".", ".", ".", "INTERNAL", "CORRESPONDENCE", "TO:", "R.", "H.", "Honeycutt", "CC:", "T.F.", "Riehl", "FROM:", "C.", "J.", "Cook", "DATE:", "May", "8.", "1995", ...
[ [ 733, 193, 791, 219 ], [ 477, 251, 567, 276 ], [ 572, 251, 592, 275 ], [ 599, 251, 756, 274 ], [ 765, 250, 881, 273 ], [ 888, 248, 1065, 274 ], [ 598, 279, 724, 303 ], [ 7...
{ "match_score": 1, "matched_text": "499150498", "start": 320, "text": "499150498" }
train_388
{ "en": "How many points are there in modifications to readout instrumentation" }
[ "5.", "5" ]
[ "2.", "The", "rotometer", "in", "the", "original", "design", "was", "replaced", "by", "a", "0-100", "SILPM", "mass", "flow", "meter", "(Hastings", "#200B)", "to", "provide", "more", "precise", "flow", "settings.", "As", "in", "the", "original", "design,", "f...
[ [ 342, 303, 363, 330 ], [ 414, 303, 461, 336 ], [ 467, 303, 584, 337 ], [ 591, 303, 619, 337 ], [ 625, 303, 665, 337 ], [ 671, 303, 774, 337 ], [ 780, 302, 857, 337 ], [ 86...
{ "match_score": 1, "matched_text": "5.", "start": 248, "text": "5." }
train_399
{ "en": "what is the date in the letter" }
[ "June 11, 1990", "June 11,1990" ]
[ "PHILIP", "MORRIS", "U.", "S.", "A.", "INTER-OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", "Dr.", "K.", "S.", "Houghton", "Date:", "June", "11,", "1990", "From:", "Ted", "Sanders", "Subject:", "Paper", "Technology", "Update", "for", "the", "Week", ...
[ [ 593, 178, 700, 211 ], [ 705, 178, 841, 211 ], [ 853, 178, 883, 210 ], [ 889, 178, 919, 210 ], [ 925, 178, 954, 210 ], [ 394, 237, 709, 272 ], [ 743, 237, 1154, 272 ], [ 6...
{ "match_score": 0.3076923191547394, "matched_text": "June", "start": 15, "text": "June 11, 1990" }
train_400
{ "en": "To whom this is addressed" }
[ "Dr.K.S.Houghton" ]
[ "PHILIP", "MORRIS", "U.", "S.", "A.", "INTER-OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", "Dr.", "K.", "S.", "Houghton", "Date:", "June", "11,", "1990", "From:", "Ted", "Sanders", "Subject:", "Paper", "Technology", "Update", "for", "the", "Week", ...
[ [ 593, 178, 700, 211 ], [ 705, 178, 841, 211 ], [ 853, 178, 883, 210 ], [ 889, 178, 919, 210 ], [ 925, 178, 954, 210 ], [ 394, 237, 709, 272 ], [ 743, 237, 1154, 272 ], [ 6...
{ "match_score": 0.5333333611488342, "matched_text": "Houghton", "start": 13, "text": "Dr.K.S.Houghton" }
train_401
{ "en": "Who sent the letter?" }
[ "Ted Sanders" ]
[ "PHILIP", "MORRIS", "U.", "S.", "A.", "INTER-OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", "Dr.", "K.", "S.", "Houghton", "Date:", "June", "11,", "1990", "From:", "Ted", "Sanders", "Subject:", "Paper", "Technology", "Update", "for", "the", "Week", ...
[ [ 593, 178, 700, 211 ], [ 705, 178, 841, 211 ], [ 853, 178, 883, 210 ], [ 889, 178, 919, 210 ], [ 925, 178, 954, 210 ], [ 394, 237, 709, 272 ], [ 743, 237, 1154, 272 ], [ 6...
{ "match_score": 0.6363636255264282, "matched_text": "Sanders", "start": 20, "text": "Ted Sanders" }
train_402
{ "en": "Which part of Virginia is this letter sent from" }
[ "Richmond" ]
[ "PHILIP", "MORRIS", "U.", "S.", "A.", "INTER-OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", "Dr.", "K.", "S.", "Houghton", "Date:", "June", "11,", "1990", "From:", "Ted", "Sanders", "Subject:", "Paper", "Technology", "Update", "for", "the", "Week", ...
[ [ 593, 178, 700, 211 ], [ 705, 178, 841, 211 ], [ 853, 178, 883, 210 ], [ 889, 178, 919, 210 ], [ 925, 178, 954, 210 ], [ 394, 237, 709, 272 ], [ 743, 237, 1154, 272 ], [ 6...
{ "match_score": 0.8888888955116272, "matched_text": "Richmond,", "start": 7, "text": "Richmond" }
train_411
{ "en": "What sort of communication/letter is this ?" }
[ "INTER-OFFICE CORRESPONDENCE" ]
[ "PHILIP", "MORRIS.", "U.", "S.", "A.", "INTER", "-", "OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", ":", "Mr.", "James", "L.", "Myracle", "Date:", "April", "27,", "1990", "From", ":", "H.", "L.", "Spielberg", "Subject:", "Flavor.", "Development", ...
[ [ 683, 96, 779, 121 ], [ 794, 96, 906, 120 ], [ 922, 96, 958, 119 ], [ 971, 97, 1005, 119 ], [ 1017, 97, 1046, 119 ], [ 432, 161, 574, 185 ], [ 591, 162, 608, 184 ], [ 620,...
{ "match_score": 0.5185185074806213, "matched_text": "CORRESPONDENCE", "start": 8, "text": "INTER-OFFICE CORRESPONDENCE" }
train_412
{ "en": "What is the date mentioned in the letter?" }
[ "April 27, 1990" ]
[ "PHILIP", "MORRIS.", "U.", "S.", "A.", "INTER", "-", "OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", ":", "Mr.", "James", "L.", "Myracle", "Date:", "April", "27,", "1990", "From", ":", "H.", "L.", "Spielberg", "Subject:", "Flavor.", "Development", ...
[ [ 683, 96, 779, 121 ], [ 794, 96, 906, 120 ], [ 922, 96, 958, 119 ], [ 971, 97, 1005, 119 ], [ 1017, 97, 1046, 119 ], [ 432, 161, 574, 185 ], [ 591, 162, 608, 184 ], [ 620,...
{ "match_score": 0.3571428656578064, "matched_text": "April", "start": 18, "text": "April 27, 1990" }
train_413
{ "en": "Which test is used to evaluate ART menthol levels that has been shipped?" }
[ "A second Danchi Test" ]
[ "PHILIP", "MORRIS.", "U.", "S.", "A.", "INTER", "-", "OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", ":", "Mr.", "James", "L.", "Myracle", "Date:", "April", "27,", "1990", "From", ":", "H.", "L.", "Spielberg", "Subject:", "Flavor.", "Development", ...
[ [ 683, 96, 779, 121 ], [ 794, 96, 906, 120 ], [ 922, 96, 958, 119 ], [ 971, 97, 1005, 119 ], [ 1017, 97, 1046, 119 ], [ 432, 161, 574, 185 ], [ 591, 162, 608, 184 ], [ 620,...
{ "match_score": 0.30000001192092896, "matched_text": "Danchi", "start": 286, "text": "A second Danchi Test" }
train_414
{ "en": "What is the subject of the document/letter?" }
[ "Flavor Development Monthly Summary for April, 1990" ]
[ "PHILIP", "MORRIS.", "U.", "S.", "A.", "INTER", "-", "OFFICE", "CORRESPONDENCE", "Richmond,", "Virginia", "To", ":", "Mr.", "James", "L.", "Myracle", "Date:", "April", "27,", "1990", "From", ":", "H.", "L.", "Spielberg", "Subject:", "Flavor.", "Development", ...
[ [ 683, 96, 779, 121 ], [ 794, 96, 906, 120 ], [ 922, 96, 958, 119 ], [ 971, 97, 1005, 119 ], [ 1017, 97, 1046, 119 ], [ 432, 161, 574, 185 ], [ 591, 162, 608, 184 ], [ 620,...
{ "match_score": 0.2199999988079071, "matched_text": "Development", "start": 28, "text": "Flavor Development Monthly Summary for April, 1990" }
train_416
{ "en": "what is the index for Retention of Franchise" }
[ "100", "(100)" ]
[ "Consumer", "Dynamics", "CARLTON", "index", ".", "Retention", "of", "Franchise:", "81.3%", "(100)", "Rate", "of", "Switching", "Losses", "9.3%", "(", "88)", "Rate", "of", "Quitting", "Losses", "9.4%", "(113)", ".", "Single", "Brand", "Users", "in", "the", "F...
[ [ 825, 313, 1158, 388 ], [ 1169, 313, 1485, 388 ], [ 999, 395, 1308, 455 ], [ 1491, 544, 1592, 581 ], [ 517, 617, 543, 657 ], [ 571, 618, 748, 658 ], [ 759, 619, 795, 658 ], [ ...
{ "match_score": 0.6000000238418579, "matched_text": "(100)", "start": 9, "text": "100" }
train_417
{ "en": "What is the source" }
[ "USMM 1/95-6/95, 12-Month Data" ]
[ "Consumer", "Dynamics", "CARLTON", "index", ".", "Retention", "of", "Franchise:", "81.3%", "(100)", "Rate", "of", "Switching", "Losses", "9.3%", "(", "88)", "Rate", "of", "Quitting", "Losses", "9.4%", "(113)", ".", "Single", "Brand", "Users", "in", "the", "F...
[ [ 825, 313, 1158, 388 ], [ 1169, 313, 1485, 388 ], [ 999, 395, 1308, 455 ], [ 1491, 544, 1592, 581 ], [ 517, 617, 543, 657 ], [ 571, 618, 748, 658 ], [ 759, 619, 795, 658 ], [ ...
{ "match_score": 0.3448275923728943, "matched_text": "1/95-6/95,", "start": 54, "text": "USMM 1/95-6/95, 12-Month Data" }
train_418
{ "en": "The number mentioned on the right of the leftside margin?" }
[ "314002838" ]
[ "Consumer", "Dynamics", "CARLTON", "index", ".", "Retention", "of", "Franchise:", "81.3%", "(100)", "Rate", "of", "Switching", "Losses", "9.3%", "(", "88)", "Rate", "of", "Quitting", "Losses", "9.4%", "(113)", ".", "Single", "Brand", "Users", "in", "the", "F...
[ [ 825, 313, 1158, 388 ], [ 1169, 313, 1485, 388 ], [ 999, 395, 1308, 455 ], [ 1491, 544, 1592, 581 ], [ 517, 617, 543, 657 ], [ 571, 618, 748, 658 ], [ 759, 619, 795, 658 ], [ ...
{ "match_score": 1, "matched_text": "314002838", "start": 51, "text": "314002838" }
train_419
{ "en": "Heading of the document" }
[ "Domestic Product Development (cont'd.)", "DOMESTIC PRODUCT DEVELOPMENT (cont'd.)", "Domestic Product Development" ]
[ "DOMESTIC", "PRODUCT", "DEVELOPMENT", "(cont'd.)", "Project", "Marlboro", "-", "POL", "0330", "-", "1.6", "tar/puff", "-", "80mm", "has", "been", "produced", "and", "currently", "is", "in", "C.I.", "for", "analytical.", "-", "POL", "0331", "-", "1.6", "tar/p...
[ [ 234, 175, 404, 209 ], [ 411, 174, 570, 209 ], [ 575, 172, 823, 209 ], [ 834, 171, 951, 207 ], [ 234, 255, 332, 289 ], [ 337, 257, 474, 289 ], [ 234, 333, 244, 367 ], [ 25...
{ "match_score": 0.28947368264198303, "matched_text": "DEVELOPMENT", "start": 2, "text": "Domestic Product Development (cont'd.)" }
train_420
{ "en": "what mm Marlboro Menthol were subjectively smoked by the Richmond Panel" }
[ "80mm and 83mm" ]
[ "DOMESTIC", "PRODUCT", "DEVELOPMENT", "(cont'd.)", "Project", "Marlboro", "-", "POL", "0330", "-", "1.6", "tar/puff", "-", "80mm", "has", "been", "produced", "and", "currently", "is", "in", "C.I.", "for", "analytical.", "-", "POL", "0331", "-", "1.6", "tar/p...
[ [ 234, 175, 404, 209 ], [ 411, 174, 570, 209 ], [ 575, 172, 823, 209 ], [ 834, 171, 951, 207 ], [ 234, 255, 332, 289 ], [ 337, 257, 474, 289 ], [ 234, 333, 244, 367 ], [ 25...
{ "match_score": 0.3076923191547394, "matched_text": "80mm", "start": 13, "text": "80mm and 83mm" }
End of preview. Expand in Data Studio
README.md exists but content is empty.
Downloads last month
34