Datasets:
prediction_ts
float32 1.65B
1.65B
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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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