prediction_ts
float32
1.65B
1.65B
language
stringclasses
1 value
split_text
sequence
ner_tags
sequence
1,650,092,416
English
[ "Atchison", ",", "Topeka", "and", "Santa", "Fe", "Railway" ]
[ 3, 4, 4, 4, 4, 4, 4 ]
1,650,092,672
English
[ "Method", "Man", "as", "Melvin", "``", "Cheese", "''", "Wagstaff" ]
[ 1, 2, 0, 1, 2, 2, 2, 2 ]
1,650,092,928
English
[ "He", "was", "the", "descendant", "of", "Mirza", "Hadi", "Baig", "." ]
[ 0, 0, 0, 0, 0, 1, 2, 2, 0 ]
1,650,093,056
English
[ "Lateran", "Palace", ",", "Lateran", "University", ",", "the", "Scala", "Santa", "and", "adjoining", "buildings", "," ]
[ 3, 4, 0, 3, 4, 0, 0, 3, 4, 0, 0, 0, 0 ]
1,650,093,312
English
[ "Prince", "William", ",", "Duke", "of", "Cambridge" ]
[ 1, 2, 2, 2, 2, 2 ]
1,650,093,568
English
[ "Ivan", "Lacković", "Croata" ]
[ 1, 2, 2 ]
1,650,093,824
English
[ "0-1", "Nicola", "Caccia", "(", "17", ")" ]
[ 0, 1, 2, 0, 0, 0 ]
1,650,094,080
English
[ "From", "1918", "to", "1946", "he", "was", "member", "of", "the", "Senate", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0 ]
1,650,094,336
English
[ "*The", "Kree", "in", "Fantastic", "Four", "''", "65" ]
[ 0, 1, 0, 1, 2, 0, 0 ]
1,650,094,464
English
[ "Drake", "and", "Josh", "''", "(", "2004-2007", ")" ]
[ 3, 4, 4, 0, 0, 0, 0 ]
1,650,094,720
English
[ "John", "Fisher", ",", "Bishop", "of", "Rochester" ]
[ 1, 2, 0, 1, 2, 2 ]
1,650,094,976
English
[ "Western", "Governors", "University" ]
[ 3, 4, 4 ]
1,650,095,232
English
[ "Lewis", "Nixon", ",", "February", "3", ",", "1919", "-", "May", "3", ",", "1919" ]
[ 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,095,488
English
[ "Rudniki", ",", "Białystok", "County" ]
[ 5, 6, 6, 6 ]
1,650,095,744
English
[ "*1280", "/", "WPKZ", ":", "Fitchburg" ]
[ 0, 0, 3, 0, 5 ]
1,650,095,872
English
[ "Peter", "Vaughan", "(", "bishop", ")" ]
[ 1, 2, 2, 2, 2 ]
1,650,096,128
English
[ "Her", "she", "came", "across", "and", "was", "encouraged", "by", "Paul", "Nash", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0 ]
1,650,096,384
English
[ "''", "Gambusia", "holbrooki", "''" ]
[ 0, 3, 4, 0 ]
1,650,096,640
English
[ "Gudja", "United", "F.C", "." ]
[ 3, 4, 4, 4 ]
1,650,096,896
English
[ "Western", "Style", "Weddings", "in", "Japan" ]
[ 3, 4, 4, 4, 4 ]
1,650,097,152
English
[ "Also", ",", "Jim", "Miller", "came", "in", "with", "only", "three", "weeks", "notice", "as", "a", "late", "replacement", "for", "Frankie", "Edgar", "against", "Matt", "Wiman", "." ]
[ 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 1, 2, 0 ]
1,650,097,408
English
[ "A", "remix", "of", "the", "track", "produced", "by", "Cedric", "Gervais", "was", "released", "on", "March", "3", ",", "2014", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,097,536
English
[ "Ben", "Zambiasi", ",", "LB" ]
[ 1, 2, 0, 0 ]
1,650,097,792
English
[ "Human", "Rights", "Commission", "of", "Malaysia" ]
[ 3, 4, 4, 4, 4 ]
1,650,098,048
English
[ "Volcanism", "of", "Western", "Canada" ]
[ 3, 4, 4, 4 ]
1,650,098,304
English
[ "1st", "Cavalry", "Division", "(", "United", "Kingdom", ")" ]
[ 3, 4, 4, 4, 4, 4, 4 ]
1,650,098,560
English
[ "Southern", "Pacific", "Transportation", "Company" ]
[ 3, 4, 4, 4 ]
1,650,098,816
English
[ "There", "are", "currently", "76", "vehicles", "available", "to", "members", ",", "with", "the", "majority", "of", "them", "located", "in", "Kitchener-Waterloo", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0 ]
1,650,098,944
English
[ "1898", "-", "Albert", "Peter", "Low" ]
[ 0, 0, 1, 2, 2 ]
1,650,099,200
English
[ "In", "August", "2006", "and", "October", "2007", "Facebook", "began", "negotiations", "to", "purchase", "StudiVZ", "'s", "websites", "." ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 3, 0, 0, 0 ]
1,650,099,456
English
[ "Vincas", "Mickevičius-Kapsukas", "(", "1919", ")" ]
[ 1, 2, 0, 0, 0 ]
1,650,099,712
English
[ "Communes", "of", "the", "Aude", "department" ]
[ 5, 6, 6, 6, 6 ]
1,650,099,968
English
[ "Luis", "Pedro", "Figueroa", "Transferred", "to", "Arsenal", "de", "Sarandí" ]
[ 1, 2, 2, 0, 0, 3, 4, 4 ]
1,650,100,224
English
[ "It", "aired", "on", "MBC", "on", "Saturdays", "and", "Sundays", "21:45", "for", "50", "episodes", "beginning", "March", "14", ",", "2015", "." ]
[ 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,100,352
English
[ "The", "Baron", "Lloyd", "of", "Berwick", "(", "1993", ")" ]
[ 0, 1, 2, 2, 2, 0, 0, 0 ]
1,650,100,608
English
[ "Hugo", "Becker", "as", "the", "student" ]
[ 1, 2, 0, 0, 0 ]
1,650,100,864
English
[ "Hans", "Hofmann", "(", "1880–1966", ")", ",", "3", "paintings", ":", "Artic" ]
[ 1, 2, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,101,120
English
[ "Glenn", "Frey", "-", "``", "Glenn", "Frey", "Live", "''", "(", "1993", ")" ]
[ 1, 2, 0, 0, 3, 4, 4, 0, 0, 0, 0 ]
1,650,101,376
English
[ "Nagahori", "Tsurumi-ryokuchi", "Line", "-", "Tamatsukuri", "Station", "or", "Tanimachi", "Rokuchōme", "Station" ]
[ 3, 4, 4, 0, 3, 4, 0, 3, 4, 4 ]
1,650,101,632
English
[ "In", "1988", "he", "had", "a", "short", "attachment", "to", "Sunday", "Sequence", "as", "presenter", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0 ]
1,650,101,888
English
[ "American", "Society", "of", "Heating", ",", "Refrigerating", "and", "Air-Conditioning", "Engineers" ]
[ 3, 4, 4, 4, 4, 4, 4, 4, 4 ]
1,650,102,016
English
[ "''", "Daydream", "Believer", "''" ]
[ 0, 3, 4, 0 ]
1,650,102,272
English
[ "Film", "and", "Television", "Institute", "of", "India" ]
[ 3, 4, 4, 4, 4, 4 ]
1,650,102,528
English
[ "Petter", "Solberg", "World", "Rally", "Team" ]
[ 3, 4, 4, 4, 4 ]
1,650,102,784
English
[ "He", "currently", "plays", "for", "Dinamo", "Brest", "." ]
[ 0, 0, 0, 0, 3, 4, 0 ]
1,650,103,040
English
[ "It", "was", "named", "after", "Ilya", "Nikolaevich", "Ulianov", ",", "an", "educator", "." ]
[ 0, 0, 0, 0, 1, 2, 2, 0, 0, 0, 0 ]
1,650,103,296
English
[ "The", "song", "has", "been", "an", "oft-covered", "song", "on", "American", "Idol", "''", "with", "singers", "Tamyra", "Gray", "and", "Fantasia", "Barrino", "covering", "it", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 1, 2, 0, 1, 2, 0, 0, 0 ]
1,650,103,424
English
[ "Ōmiya", "Station", "(", "Kyoto", ")" ]
[ 3, 4, 4, 4, 4 ]
1,650,103,680
English
[ "Paul", "IV", "of", "Constantinople" ]
[ 1, 2, 2, 2 ]
1,650,103,936
English
[ "Welcome", "to", "Blue", "Island", "(", "2003", ")" ]
[ 3, 4, 4, 4, 0, 0, 0 ]
1,650,104,192
English
[ "Altes", "Theater", "(", "Leipzig", ")" ]
[ 3, 4, 4, 4, 4 ]
1,650,104,448
English
[ "She", "was", "the", "model", "for", "quite", "a", "few", "of", "Edvard", "Munch", "'s", "paintings", "." ]
[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0 ]
1,650,104,704
English
[ "Cecil", "Calvert", ",", "2nd", "Baron", "Baltimore" ]
[ 1, 2, 2, 2, 2, 2 ]
1,650,104,832
English
[ "It", "was", "formed", "in", "1994", "from", "the", "amalgamation", "of", "parts", "of", "the", "Shire", "of", "Euroa", ",", "Shire", "of", "Goulburn", ",", "Shire", "of", "Violet", "Town", ",", "Shire", "of", "McIvor", "and", "Rural", "City", "of", "Seymour", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 0, 5, 6, 6, 0, 5, 6, 6, 6, 0, 5, 6, 6, 0, 5, 6, 6, 6, 0 ]
1,650,105,088
English
[ "National", "Register", "of", "Historic", "Places", "listings", "in", "Cumberland", "County", ",", "Maine" ]
[ 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
1,650,105,344
English
[ "Lew", "Dietz", ",", "writer" ]
[ 1, 2, 0, 0 ]
1,650,105,600
English
[ "Peter", "Sandhu5,446", "(", "39.58", "%", ")" ]
[ 1, 2, 0, 0, 0, 0 ]
1,650,105,856
English
[ "Sathnam", "Sanghera", "-", "journalist", "and", "author" ]
[ 1, 2, 0, 0, 0, 0 ]
1,650,106,112
English
[ "four", "segments", ",", "all", "written", "by", "Tonino", "Guerra" ]
[ 0, 0, 0, 0, 0, 0, 1, 2 ]
1,650,106,240
English
[ "For", "more", "information", "on", "this", "creation", ",", "see", "Duke", "of", "Argyll", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 0 ]
1,650,106,496
English
[ "Shin'ya", "Fujiwara", ",", "Issei", "Suda" ]
[ 1, 2, 0, 1, 2 ]
1,650,106,752
English
[ "All", "Star", "(", "song", ")" ]
[ 3, 4, 4, 4, 4 ]
1,650,107,008
English
[ "Maurice", "Béjart", "(", "1927–2007", ")", ",", "elected", "in", "1994" ]
[ 1, 2, 0, 0, 0, 0, 0, 0, 0 ]
1,650,107,264
English
[ "Maryland", "Route", "47" ]
[ 3, 4, 4 ]
1,650,107,520
English
[ "Head", "of", "government", ":", "Prime", "Minister", "of", "Andorra" ]
[ 1, 2, 2, 0, 3, 4, 4, 4 ]
1,650,107,776
English
[ "He", "replaced", "Nicolas", "Maurice-Belay", "after", "87", "minutes", "in", "a", "2-1", "defeat", "." ]
[ 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,107,904
English
[ "``", "Knock", "Three", "Times", "''" ]
[ 0, 3, 4, 4, 0 ]
1,650,108,160
English
[ "James", "W.", "Faulkner", "political", "journalist" ]
[ 1, 2, 2, 0, 0 ]
1,650,108,416
English
[ "Semi", "Chellas", ",", "Matthew", "Weiner" ]
[ 1, 2, 0, 1, 2 ]
1,650,108,672
English
[ "Adrian", "Mannarino", "won", "the", "title", ",", "defeating", "Mikhail", "Kukushkin", "6–4", ",", "3–6", ",", "6–3", "in", "the", "final", "." ]
[ 1, 2, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,108,928
English
[ "''", "Coronation", "Street", "''", "(", "3", "episodes", ",", "1988", ")" ]
[ 0, 3, 4, 0, 0, 0, 0, 0, 0, 0 ]
1,650,109,184
English
[ "composed", ",", "written", "and", "performed", "by", "Miyuki", "Nakajima", "(", "episode", "19", ")" ]
[ 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0 ]
1,650,109,312
English
[ "Lego", "Media", "established", "by", "Lego", "Group" ]
[ 3, 4, 0, 0, 1, 2 ]
1,650,109,568
English
[ "This", "song", "was", "produced", "by", "Dan", "Muckala", "." ]
[ 0, 0, 0, 0, 0, 1, 2, 0 ]
1,650,109,824
English
[ "'", "''", "Syd", "Ball", "''", "'", "'", "''", "Cliff", "Letcher", "''", "'", "6-3", ",", "6-4" ]
[ 0, 0, 1, 2, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0 ]
1,650,110,080
English
[ "William", "Dowling", "(", "disambiguation", ")", ",", "multiple", "people" ]
[ 3, 4, 4, 4, 4, 0, 0, 0 ]
1,650,110,336
English
[ "It", "began", "on", "2", "April", "at", "Motegi", "and", "ended", "on", "23", "October", "at", "the", "same", "place", "." ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,110,592
English
[ "Henri", ",", "Duke", "of", "Joyeuse" ]
[ 1, 2, 2, 2, 2 ]
1,650,110,720
English
[ "Campagnolo", "–", "from", "the", "name", "of", "its", "founder", ",", "Tullio", "Campagnolo", "." ]
[ 3, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0 ]
1,650,110,976
English
[ "Subsequently", "he", "went", "to", "Lincoln", "University", "." ]
[ 0, 0, 0, 0, 3, 4, 0 ]
1,650,111,232
English
[ "Rodrigo", "Rojas", "DeNegri" ]
[ 1, 2, 2 ]
1,650,111,488
English
[ "In", "addition", ",", "he", "was", "able", "to", "obtain", "recognition", "of", "his", "son", ",", "Aedh", "mac", "Cathal", "Crobdearg", "Ua", "Conchobair", "as", "his", "heir", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 4, 4, 4, 0, 0, 0, 0 ]
1,650,111,744
English
[ "Otaku", "no", "Seiza", ":", "An", "Adventure", "in", "the", "Otaku", "Galaxy" ]
[ 3, 4, 4, 4, 4, 4, 4, 4, 3, 4 ]
1,650,112,000
English
[ "Margaret", "Court", "Lesley", "Turner", "Bowrey" ]
[ 1, 2, 1, 2, 2 ]
1,650,112,256
English
[ "Ali", "III", "ibn", "al-Husayn" ]
[ 1, 2, 2, 2 ]
1,650,112,384
English
[ "Pyramidal", "process", "of", "palatine", "bone", "(", "processus", "pyramidalis", "ossis", "palatini", ")" ]
[ 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6 ]
1,650,112,640
English
[ "He", "was", "the", "son", "of", "William", "II", "of", "Dampierre", "and", "Margaret", "II", "of", "Flanders", "." ]
[ 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 3, 4, 4, 4, 0 ]
1,650,112,896
English
[ "Aaron", "Copland", ",", "composer" ]
[ 1, 2, 0, 0 ]
1,650,113,152
English
[ "*Lifetime", "Achievement", "-", "Arthur", "M.", "Schlesinger", ",", "Jr", "." ]
[ 0, 0, 0, 1, 2, 2, 2, 2, 2 ]
1,650,113,408
English
[ "''", "Khmer", "Empire", "''", "'", "–", "Jayavarman", "II", "(", "802–850", ")" ]
[ 0, 5, 6, 0, 0, 0, 1, 2, 0, 0, 0 ]
1,650,113,664
English
[ "Tupac", "A.", "Hunter" ]
[ 1, 2, 2 ]
1,650,113,792
English
[ "He", "replaced", "Gary", "Robichaud", "as", "leader", "." ]
[ 0, 0, 1, 2, 0, 0, 0 ]
1,650,114,048
English
[ "Finta", ",", "Dâmbovița" ]
[ 5, 6, 6 ]
1,650,114,304
English
[ "United", "Kingdom", "Energy", "Technologies", "Institute" ]
[ 3, 4, 4, 4, 4 ]
1,650,114,560
English
[ "Cars", "were", "entered", "for", "Russ", "Snowberger", ",", "Ted", "Horn", "and", "George", "Connor", "." ]
[ 0, 0, 0, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0 ]
1,650,114,816
English
[ "1913-1921", ":", "Albert", "Besnard" ]
[ 0, 0, 3, 4 ]
1,650,115,072
English
[ "Cyborg", "(", "voiced", "by", "Khary", "Payton", ")" ]
[ 1, 0, 0, 0, 1, 2, 0 ]
1,650,115,200
English
[ "Ian", "Woosnam", "(", "2", ")" ]
[ 1, 2, 0, 0, 0 ]
1,650,115,456
English
[ "Another", "notable", "feature", "of", "this", "song", "was", "the", "lyrics", "by", "O.", "N.", "V.", "Kurup", ",", "who", "for", "the", "first", "time", "wrote", "lyrics", "for", "a", "pre-composed", "song", "." ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
1,650,115,712
English
[ "Southern", "Amalgamated", "Workers", "'", "Union" ]
[ 3, 4, 4, 4, 4 ]

Dataset Card for reviews_with_drift

Dataset Description

Dataset Summary

This dataset was crafted to be used in our tutorial [Link to the tutorial when ready]. It consists on a large Movie Review Dataset mixed with some reviews from a Hotel Review Dataset. The training/validation set are purely obtained from the Movie Review Dataset while the production set is mixed. Some other features have been added (age, gender, context) as well as a made up timestamp prediction_ts of when the inference took place.

Supported Tasks and Leaderboards

text-classification, sentiment-classification: The dataset is mainly used for text classification: given the text, predict the sentiment (positive or negative).

Languages

Text is mainly written in english.

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

[More Information Needed]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

Thanks to @fjcasti1 for adding this dataset.

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