Datasets:
sst2

Task Categories: text-classification
Languages: English
Multilinguality: monolingual
Size Categories: 10K<n<100K
Language Creators: found
Annotations Creators: crowdsourced
Source Datasets: original
Licenses: unknown
Dataset Preview Go to dataset viewer
idx (int)sentence (string)label (class label)
0
hide new secretions from the parental units
0 (negative)
1
contains no wit , only labored gags
0 (negative)
2
that loves its characters and communicates something rather beautiful about human nature
1 (positive)
3
remains utterly satisfied to remain the same throughout
0 (negative)
4
on the worst revenge-of-the-nerds clichés the filmmakers could dredge up
0 (negative)
5
that 's far too tragic to merit such superficial treatment
0 (negative)
6
demonstrates that the director of such hollywood blockbusters as patriot games can still turn out a small , personal film with an emotional wallop .
1 (positive)
7
of saucy
1 (positive)
8
a depressed fifteen-year-old 's suicidal poetry
0 (negative)
9
are more deeply thought through than in most ` right-thinking ' films
1 (positive)
10
goes to absurd lengths
0 (negative)
11
for those moviegoers who complain that ` they do n't make movies like they used to anymore
0 (negative)
12
the part where nothing 's happening ,
0 (negative)
13
saw how bad this movie was
0 (negative)
14
lend some dignity to a dumb story
0 (negative)
15
the greatest musicians
1 (positive)
16
cold movie
0 (negative)
17
with his usual intelligence and subtlety
1 (positive)
18
redundant concept
0 (negative)
19
swimming is above all about a young woman 's face , and by casting an actress whose face projects that woman 's doubts and yearnings , it succeeds .
1 (positive)
20
equals the original and in some ways even betters it
1 (positive)
21
if anything , see it for karen black , who camps up a storm as a fringe feminist conspiracy theorist named dirty dick .
1 (positive)
22
a smile on your face
1 (positive)
23
comes from the brave , uninhibited performances
1 (positive)
24
excruciatingly unfunny and pitifully unromantic
0 (negative)
25
enriched by an imaginatively mixed cast of antic spirits
1 (positive)
26
which half of dragonfly is worse : the part where nothing 's happening , or the part where something 's happening
0 (negative)
27
in world cinema
1 (positive)
28
very good viewing alternative
1 (positive)
29
the plot is nothing but boilerplate clichés from start to finish ,
0 (negative)
30
the action is stilted
0 (negative)
31
on all cylinders
1 (positive)
32
will find little of interest in this film , which is often preachy and poorly acted
0 (negative)
33
by far the worst movie of the year
0 (negative)
34
sit through ,
0 (negative)
35
more than another `` best man '' clone by weaving a theme throughout this funny film
1 (positive)
36
it 's about issues most adults have to face in marriage and i think that 's what i liked about it -- the real issues tucked between the silly and crude storyline
1 (positive)
37
heroes
1 (positive)
38
oblivious to the existence of this film
0 (negative)
39
sharply
1 (positive)
40
the entire point of a shaggy dog story , of course , is that it goes nowhere , and this is classic nowheresville in every sense .
0 (negative)
41
sometimes dry
0 (negative)
42
as they come , already having been recycled more times than i 'd care to count
0 (negative)
43
covers this territory with wit and originality , suggesting that with his fourth feature
1 (positive)
44
a $ 40 million version of a game
0 (negative)
45
gorgeous and deceptively minimalist
1 (positive)
46
cross swords with the best of them and
1 (positive)
47
as a fringe feminist conspiracy theorist
0 (negative)
48
proves once again he has n't lost his touch , bringing off a superb performance in an admittedly middling film .
1 (positive)
49
disappointments
0 (negative)
50
the horrors
0 (negative)
51
a muddle splashed with bloody beauty as vivid as any scorsese has ever given us .
1 (positive)
52
many pointless
0 (negative)
53
a beautifully
1 (positive)
54
contrived , well-worn situations
0 (negative)
55
a doa
0 (negative)
56
poor ben bratt could n't find stardom if mapquest emailed him point-to-point driving directions .
0 (negative)
57
to be as subtle and touching as the son 's room
1 (positive)
58
starts with a legend
1 (positive)
59
far less sophisticated and
0 (negative)
60
rich veins of funny stuff in this movie
1 (positive)
61
no apparent joy
0 (negative)
62
shot on ugly digital video
0 (negative)
63
... a sour little movie at its core ; an exploration of the emptiness that underlay the relentless gaiety of the 1920 's ... the film 's ending has a `` what was it all for ? ''
0 (negative)
64
though ford and neeson capably hold our interest , but its just not a thrilling movie
0 (negative)
65
is pretty damned funny .
1 (positive)
66
we never feel anything for these characters
0 (negative)
67
's a lousy one at that
0 (negative)
68
the corporate circus that is the recording industry in the current climate of mergers and downsizing
0 (negative)
69
the storylines are woven together skilfully , the magnificent swooping aerial shots are breathtaking , and the overall experience is awesome .
1 (positive)
70
of the most highly-praised disappointments i
0 (negative)
71
sounds like a cruel deception carried out by men of marginal intelligence , with reactionary ideas about women and a total lack of empathy .
0 (negative)
72
seem fresh
1 (positive)
73
to the dustbin of history
0 (negative)
74
as a director , eastwood is off his game
0 (negative)
75
pays earnest homage to turntablists
1 (positive)
76
weak and
0 (negative)
77
skip this dreck ,
0 (negative)
78
contains very few laughs and even less surprises
0 (negative)
79
film to affirm love 's power to help people endure almost unimaginable horror
1 (positive)
80
are an absolute joy
1 (positive)
81
generates
1 (positive)
82
, like life , is n't much fun without the highs and lows
1 (positive)
83
based on a true and historically significant story
1 (positive)
84
well-rounded tribute
1 (positive)
85
, though many of the actors throw off a spark or two when they first appear , they ca n't generate enough heat in this cold vacuum of a comedy to start a reaction .
0 (negative)
86
so much like a young robert deniro
1 (positive)
87
khouri manages , with terrific flair , to keep the extremes of screwball farce and blood-curdling family intensity on one continuum .
1 (positive)
88
fashioning an engrossing entertainment out
1 (positive)
89
spiffy animated feature
1 (positive)
90
that 's so sloppily written and cast that you can not believe anyone more central to the creation of bugsy than the caterer
0 (negative)
91
alternating between facetious comic parody and pulp melodrama , this smart-aleck movie ... tosses around some intriguing questions about the difference between human and android life
1 (positive)
92
strung-together moments
0 (negative)
93
, generous and subversive artworks
1 (positive)
94
it does n't follow the stale , standard , connect-the-dots storyline which has become commonplace in movies that explore the seamy underbelly of the criminal world
1 (positive)
95
funny yet
1 (positive)
96
overbearing and over-the-top
0 (negative)
97
it 's robert duvall !
1 (positive)
98
rich and sudden wisdom
1 (positive)
99
acted and directed , it 's clear that washington most certainly has a new career ahead of him
1 (positive)
End of preview (truncated to 100 rows)

Dataset Card for [Dataset Name]

Dataset Summary

The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language. The corpus is based on the dataset introduced by Pang and Lee (2005) and consists of 11,855 single sentences extracted from movie reviews. It was parsed with the Stanford parser and includes a total of 215,154 unique phrases from those parse trees, each annotated by 3 human judges.

Binary classification experiments on full sentences (negative or somewhat negative vs somewhat positive or positive with neutral sentences discarded) refer to the dataset as SST-2 or SST binary.

Supported Tasks and Leaderboards

  • sentiment-classification

Languages

The text in the dataset is in English (en).

Dataset Structure

Data Instances

{'idx': 0,
 'sentence': 'hide new secretions from the parental units ',
 'label': 0}

Data Fields

  • idx: Monotonically increasing index ID.
  • sentence: Complete sentence expressing an opinion about a film.
  • label: Sentiment of the opinion, either "negative" (0) or positive (1).

Data Splits

train validation test
Number of examples 67349 872 1821

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

Rotten Tomatoes reviewers.

Annotations

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

Unknown.

Citation Information

@inproceedings{socher-etal-2013-recursive,
    title = "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank",
    author = "Socher, Richard  and
      Perelygin, Alex  and
      Wu, Jean  and
      Chuang, Jason  and
      Manning, Christopher D.  and
      Ng, Andrew  and
      Potts, Christopher",
    booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing",
    month = oct,
    year = "2013",
    address = "Seattle, Washington, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D13-1170",
    pages = "1631--1642",
}

Contributions

Thanks to @albertvillanova for adding this dataset.

Models trained or fine-tuned on sst2

Spaces using sst2