---
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.