同步操作将从 Hugging Face 数据集镜像/sst 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!!
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sst |
Stanford Sentiment Treebank |
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The Stanford Sentiment Treebank is the first corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.
sentiment-scoring
: Each complete sentence is annotated with a float
label that indicates its level of positive sentiment from 0.0 to 1.0. One can decide to use only complete sentences or to include the contributions of the sub-sentences (aka phrases). The labels for each phrase are included in the dictionary
configuration. To obtain all the phrases in a sentence we need to visit the parse tree included with each example. In contrast, the ptb
configuration explicitly provides all the labelled parse trees in Penn Treebank format. Here the labels are binned in 5 bins from 0 to 4.sentiment-classification
: We can transform the above into a binary sentiment classification task by rounding each label to 0 or 1.The text in the dataset is in English
For the default
configuration:
{'label': 0.7222200036048889,
'sentence': 'Yet the act is still charming here .',
'tokens': 'Yet|the|act|is|still|charming|here|.',
'tree': '15|13|13|10|9|9|11|12|10|11|12|14|14|15|0'}
For the dictionary
configuration:
{'label': 0.7361099720001221,
'phrase': 'still charming'}
For the ptb
configuration:
{'ptb_tree': '(3 (2 Yet) (3 (2 (2 the) (2 act)) (3 (4 (3 (2 is) (3 (2 still) (4 charming))) (2 here)) (2 .))))'}
sentence
: a complete sentence expressing an opinion about a filmlabel
: the degree of "positivity" of the opinion, on a scale between 0.0 and 1.0tokens
: a sequence of tokens that form a sentencetree
: a sentence parse tree formatted as a parent pointer treephrase
: a sub-sentence of a complete sentenceptb_tree
: a sentence parse tree formatted in Penn Treebank-style, where each component's degree of positive sentiment is labelled on a scale from 0 to 4The set of complete sentences (both default
and ptb
configurations) is split into a training, validation and test set. The dictionary
configuration has only one split as it is used for reference rather than for learning.
[Needs More Information]
[Needs More Information]
Rotten Tomatoes reviewers.
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@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",
}
Thanks to @patpizio for adding this dataset.
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