File size: 2,232 Bytes
50288fa
 
f9bd110
 
 
 
 
 
 
 
 
714e033
 
 
 
ec31c70
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
92a2849
 
 
 
ec31c70
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9ae8cde
4cf7aa9
ec31c70
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
---
license: mit
language:
- en
tags:
- history
- philosophy
- art
pretty_name: Historical Quotes - English
size_categories:
- 10K<n<100K
task_categories:
- text-classification
- conversational
- fill-mask
---
Dataset Card for English Historical Quotes

# I-Dataset Summary

english_historical_quotes is a dataset of many historical quotes.
This dataset can be used for multi-label text classification and text generation. The content of each quote is in English.

# II-Supported Tasks and Leaderboards

    Multi-label text classification : The dataset can be used to train a model for text-classification, which consists of classifying quotes by author as well as by topic (using tags). Success on this task is typically measured by achieving a high or low accuracy.
    Text-generation : The dataset can be used to train a model to generate quotes by fine-tuning an existing pretrained model on the corpus composed of all quotes (or quotes by author).

# III-Languages

The texts in the dataset are in English (en).

# IV-Dataset Structure
Data Instances

A JSON-formatted example of a typical instance in the dataset:

 {"quote":"Almost anyone can be an author the business is to collect money and fame from this state of being.",
"author":"A. A. Milne",
"categories": "['business', 'money']"
}

### Data Fields

    author : The author of the quote.
    quote : The text of the quote.
    tags: The tags could be characterized as topics around the quote.

### Data Splits

The dataset is one block, so that it can be further processed using Hugging Face `datasets` functions like the ``.train_test_split() method.

# V-Dataset Creation
Curation Rationale

The goal is to share good datasets with the HuggingFace community so that they can use them in NLP tasks and advance artificial intelligence.

### Source Data

The data has been aggregated from various open-access internet archives. Then it has been manually refined, duplicates and false quotes removed by me.

It is the backbone of my website [dixit.app](http://dixit.app), which allows to search historical quotes through semantic search.

# VI-Additional Informations
Dataset Curators

Aymeric Roucher

Licensing Information
This work is licensed under a MIT License.