File size: 2,871 Bytes
fa224fb |
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 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
---
dataset_info:
features:
- name: id
dtype: string
- name: poem_id
dtype: int64
- name: poet
dtype: string
- name: dynasty
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: setiments
dtype: string
splits:
- name: train
num_bytes: 474283
num_examples: 4000
- name: test
num_bytes: 127061
num_examples: 1000
download_size: 1865728
dataset_size: 601344
configs:
- config_name: default
data_files:
- split: train
path: train-*.parquet
- split: test
path: test-*.parquet
---
# FSPC - Fine-grained Sentimental Poetry Corpus
FSPC is a manually-labelled Fine-grained Sentiment Poetry Corpus. Each poem and each line is annotated into 5 classes, namely negative, implicit negative, neutral, implicit positive and positive.
## Dataset Information
- **Version**: V1.0
- **Number of poems**: 5,000
- **Sentiment Classes**:
- 1: negative
- 2: implicit negative
- 3: neutral
- 4: implicit positive
- 5: positive
## Data Format
The dataset is stored in Parquet format with the following fields:
- `id`: Unique identifier (poem_id as string)
- `poem_id`: Poem sequence number
- `poet`: Poet name
- `dynasty`: Dynasty name (e.g., "唐", "宋")
- `title`: Poem title
- `text`: Full poem text with lines separated by newline characters (original "|" replaced with "
")
- `setiments`: JSON string containing sentiment labels in original format: `{"holistic": "1", "line1": "1", "line2": "1", "line3": "2", "line4": "2"}`
The dataset is split into train (80%) and test (20%) sets with stratified sampling based on holistic sentiment to ensure balanced distribution.
## Citation
If you use this corpus, please cite the following paper:
```
@inproceedings{chensentiment:19,
author = {Huimin Chen and Xiaoyuan Yi and Maosong Sun and Cheng Yang and Wenhao Li and Zhipeng Guo},
title = {Sentiment-Controllable Chinese Poetry Generation},
year = "2019",
booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence},
address = {Macao, China}
}
```
## Original Dataset
The original dataset can be found in JSON format where each line is a poem with the following structure:
```json
{
"poet": "韦庄",
"poem": "自有春愁正断魂|不堪芳草思王孙|落花寂寂黄昏雨|深院无人独倚门",
"dynasty": "唐",
"setiments": {"holistic": "1", "line1": "1", "line2": "1", "line3": "2", "line4": "2"},
"title": "春愁"
}
```
Lines and sentiments in a poem are split by "|". The sentiments dict contains the holistic sentiment of whole poem, sentiment of the first line, ..., sentiment of the fourth line.
|