Stanford Sentiment Treebank V1.0数据集

Stanford Sentiment Treebank V1.0数据集

原文：

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher Manning, Andrew Ng and Christopher Potts

Conference on Empirical Methods in Natural Language Processing (EMNLP 2013)

his file includes:

1. original_rt_snippets.txt contains 10,605 processed snippets from the original pool of Rotten Tomatoes HTML files. Please note that some snippet may contain multiple sentences.

2. dictionary.txt contains all phrases and their IDs, separated by a vertical line

3. sentiment_labels.txt contains all phrase ids and the corresponding sentiment labels, separated by a vertical line.

Note that you can recover the 5 classes by mapping the positivity probability using the following cut-offs:

[0, 0.2], (0.2, 0.4], (0.4, 0.6], (0.6, 0.8], (0.8, 1.0]

for very negative, negative, neutral, positive, very positive, respectively.

Please note that phrase ids and sentence ids are not the same.

4. SOStr.txt and STree.txt encode the structure of the parse trees.

STree encodes the trees in a parent pointer format. Each line corresponds to each sentence in the datasetSentences.txt file. The Matlab code of this paper will show you how to read this format if you are not familiar with it.

5. datasetSentences.txt contains the sentence index, followed by the sentence string separated by a tab. These are the sentences of the train/dev/test sets.

6. datasetSplit.txt contains the sentence index (corresponding to the index in datasetSentences.txt file) followed by the set label separated by a comma:

1 = train

2 = test

3 = dev

译：

情绪回溯语义合成的递归深层模型

Richard Socher、Alex Perelygin、Jean Wu、Jason Chuang、Christopher Manning、Andrew Ng和Christopher Potts

自然语言处理经验方法会议（EMNLP 2013）

文件包括：

1、original_rt_snippets.txt包含10605个处理过的片段注意，某些片段可能包含多个句子。

2、dictionary.txt包含所有短语及其ID，用垂直线分隔。

3、sentiment_labels.txt包含所有短语ID和相应的情感标签，用垂直线分隔。

注意，您可以通过使用以下截断映射正概率来恢复5个类：

[0,0.2]，（0.2，0.4]，（0.4，0.6]，（0.6，0.8]，（0.8，1.0]

对于非常消极、消极、中立、积极、非常积极的人，分别。

请注意短语ID和句子ID不相同。

4、SOStr.txt以及STree.txt对解析树的结构进行编码。

STree以父指针格式对树进行编码。每行对应于datasetSentences.txt文件。

5、datasetSentences.txt包含句子索引，后面是由选项卡分隔的句子字符串。这些是train/dev/testset的句子。

6、datasetSplit.txt包含句子索引（与中的索引相对应dataset句子.txt文件）后面是用逗号分隔的集合标签：

1 = train

2 = test

3 = dev

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