---
license: other
license_name: academic-use-only-thuaipoet
license_link: https://github.com/THUNLP-AIPoet/Datasets
task_categories:
- text-classification
task_ids:
- multi-class-classification
language:
- zh
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
pretty_name: FSPC (Fine-grained Sentimental Poetry Corpus)
tags:
- poetry
- chinese
- classical-chinese
- sentiment-classification
- fine-grained-sentiment
- multi-class-classification
- mteb
- poetrymteb
- embedding-evaluation
annotations_creators:
- expert-generated
source_datasets:
- THUNLP-AIPoet/Datasets
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  default: true
dataset_info:
- config_name: default
  features:
  - name: id
    dtype: string
  - name: poem_id
    dtype: int64
  - name: title
    dtype: string
  - name: poet
    dtype: string
  - name: dynasty
    dtype: string
  - name: poem
    dtype: string
  - name: label
    dtype: int64
  - name: label_name
    dtype: string
  - name: line_labels
    sequence: int64
  - name: line_label_names
    sequence: string
  - name: sentiments
    dtype: string
  splits:
  - name: train
    num_examples: 4000
  - name: test
    num_examples: 1000
---

# FSPC — Fine-grained Sentimental Poetry Corpus

Manually labelled **fine-grained sentiment** classification of **classical Chinese poetry** for PoetryMTEB embedding evaluation.

Upstream FSPC (THU-FSPC) annotates each poem and each line into five sentiment classes (negative → positive, including implicit polarity). Source: [THUNLP-AIPoet/Datasets/FSPC](https://github.com/THUNLP-AIPoet/Datasets/tree/master/FSPC) ([mirror](https://github.com/MrQianJinSi/Datasets/tree/master/FSPC)).

## Dataset Card

| Item | Description |
|------|-------------|
| **Dataset version (PoetryMTEB)** | `1.0.0` |
| **Upstream version** | V1.0 (5,000 poems) |
| **Source** | [THUNLP-AIPoet/Datasets/FSPC](https://github.com/THUNLP-AIPoet/Datasets/tree/master/FSPC) |
| **Paper** | Chen et al., *Sentiment-Controllable Chinese Poetry Generation*, IJCAI 2019 ([pdf](https://www.ijcai.org/proceedings/2019/0695.pdf)) |
| **Languages** | Classical Chinese / Chinese (`zh`) |
| **Unit** | Full poem text (`poem`); lines originally `|`-separated, stored with newlines |
| **Labels** | Single-label **5-class** holistic sentiment (`label` / `label_name`); line-level labels also provided |
| **Size** | train=4000; test=1000; **total=5000** |
| **Splits** | **train / test only** (no validation). Poem membership preserved from the previous PoetryMTEB/FSPC release (stratified by holistic sentiment, ~80/20) |
| **License** | **Academic use only** (THUAIPoet Datasets release note). Cite the original paper. |
| **Evaluation metrics** | Embedding classification: **accuracy**, **macro/micro F1** (see `scripts/evaluate_fspc.py`) |

## Label taxonomy (5)

| id | upstream | label_name | name_zh | name_en | train | test | total |
|---:|---------:|------------|---------|---------|------:|-----:|------:|
| 0 | 1 | `negative` | 消极 | negative | 231 | 58 | 289 |
| 1 | 2 | `implicit_negative` | 隐式消极 | implicit negative | 1173 | 293 | 1466 |
| 2 | 3 | `neutral` | 中性 | neutral | 1062 | 266 | 1328 |
| 3 | 4 | `implicit_positive` | 隐式积极 | implicit positive | 1250 | 312 | 1562 |
| 4 | 5 | `positive` | 积极 | positive | 284 | 71 | 355 |

Codebook: `label_taxonomy.json`. Upstream field name `setiments` is a known typo; this packaging stores the same JSON under `sentiments`.

## Features

| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Example id (`fspc-{split}-{poem_id}`) |
| `poem_id` | int64 | 1-based index in upstream `FSPC_V1.0.json` order |
| `title` | string | Poem title |
| `poet` | string | Poet name |
| `dynasty` | string | Dynasty |
| `poem` | string | **Classification input**: full poem body (newlines between lines) |
| `label` | int64 | Holistic sentiment class id (0–4) |
| `label_name` | string | Holistic class name |
| `line_labels` | list[int64] | Per-line class ids (usually 4) |
| `line_label_names` | list[string] | Per-line class names |
| `sentiments` | string | Original sentiment dict as JSON (`holistic`, `line1`…`line4` with upstream codes 1–5) |

Schema aligns with other PoetryMTEB classification datasets (`id`, `poem`, `label`, `label_name`).

## Construction method

1. Download upstream `FSPC_V1.0.json` (JSON Lines, 5,000 poems).
2. Map `|` line separators → newlines; map upstream codes 1–5 → ids 0–4.
3. Assign **train/test** using poem_id membership from the prior `PoetryMTEB/FSPC` release (**no validation split**).
4. Write parquet shards, `dataset_infos.yaml`, Dataset Card, split id lists, checksums, eval script, and annotation prompt template.

## Supporting materials (this repo)

| Path | Content |
|------|---------|
| `VERSION` | PoetryMTEB packaging version |
| `LICENSE` | Academic-use-only notice |
| `CITATION.cff` / `CITATION.bib` | Citation metadata |
| `metadata.json` | Dataset metadata |
| `label_taxonomy.json` | Label codebook + counts |
| `splits/train_ids.txt` / `splits/test_ids.txt` | Split poem_id lists |
| `checksums.sha256` | SHA256 of packaged files |
| `prompts/annotation_prompt_template.md` | Reconstructed annotation guideline template |
| `scripts/evaluate_fspc.py` | Baseline probe evaluation (accuracy / F1) |

## How to load

```python
from datasets import load_dataset

ds = load_dataset("PoetryMTEB/FSPC")
print(ds["train"][0]["poem"])
print(ds["train"][0]["label_name"], ds["train"][0]["label"])
```

## Intended use

- PoetryMTEB / MTEB-style **multi-class classification** probing of classical Chinese poem embeddings (fine-grained sentiment).
- Research on implicit sentiment in classical Chinese poetry.

**Not for commercial use** without permission from the original data providers.

## Citation

```bibtex
@inproceedings{chensentiment19,
  author    = {Huimin Chen and Xiaoyuan Yi and Maosong Sun and Cheng Yang and Wenhao Li and Zhipeng Guo},
  title     = {Sentiment-Controllable Chinese Poetry Generation},
  booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI)},
  year      = {2019},
  address   = {Macao, China}
}
```

Upstream: [https://github.com/THUNLP-AIPoet/Datasets/tree/master/FSPC](https://github.com/THUNLP-AIPoet/Datasets/tree/master/FSPC)

This Hub packaging: `PoetryMTEB/FSPC` (version 1.0.0)

## License

Redistributed for **academic research only**, following the [THUAIPoet Datasets](https://github.com/THUNLP-AIPoet/Datasets) release note. Please cite the IJCAI 2019 paper when using the data.