Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
multi-class-classification
Languages:
English
Size:
1K - 10K
License:
File size: 5,009 Bytes
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license: cc-by-sa-4.0
task_categories:
- text-classification
task_ids:
- multi-class-classification
language:
- en
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
pretty_name: English Poetry Form Classification
tags:
- poetry
- english
- form-classification
- poetic-form
- text-classification
- mteb
- poetrymteb
- embedding-evaluation
annotations_creators:
- found
source_datasets:
- riazhsks/multilingual-annotated-poems
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
dtype: string
- name: title
dtype: string
- name: author
dtype: string
- name: label
dtype: int64
- name: label_name
dtype: string
splits:
- name: train
num_examples: 1080
- name: test
num_examples: 271
---
# English Poetry Form Classification
Single-label **English poetic form classification** for PoetryMTEB embedding evaluation, derived from the English corpus in [multilingual-annotated-poems](https://github.com/riazhsks/multilingual-annotated-poems) (originally based on [poetry-eval](https://github.com/maria-antoniak/poetry-eval) / Walsh et al., EMNLP Findings 2024).
## Dataset Card
| Item | Description |
|------|-------------|
| **Source** | [https://github.com/riazhsks/multilingual-annotated-poems](https://github.com/riazhsks/multilingual-annotated-poems) → `corpora/english_poems_processed.jsonl` |
| **Languages** | English (`en`) |
| **Size** | train=1080; test=271 (no validation; MTEB Classification: train→fit, test→score) |
| **Classes** | 15 forms with frequency ≥ 10 |
| **Filtering** | Drop empty/`null` form; poem length ∈ [40, 8000] chars; rare forms (count < 10) |
| **Splits** | Stratified by form ≈ 80% / 19%, seed=42 |
| **License** | [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) (upstream CC-BY-SA) |
| **Dataset version** | `1.0.0` |
| **Evaluation metrics** | Classification on embeddings: **accuracy**, **macro/weighted F1** |
## Features
| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Example id |
| `poem` | string | Poem text (classification input) |
| `title` | string | Title (metadata) |
| `author` | string | Author (metadata) |
| `label` | int64 | Form class index 0 … C−1 |
| `label_name` | string | Form name |
Codebook: `label_taxonomy.json`.
### Label inventory (kept)
| id | label_name | gloss | train | test | total* |
|---:|------------|-------|------:|-----:|-------:|
| 0 | `sonnet` | Sonnet (十四行) | 468 | 117 | 585 |
| 1 | `couplet` | Couplet (对句) | 220 | 55 | 275 |
| 2 | `common measure` | Common measure (通用格) | 55 | 14 | 69 |
| 3 | `ballad` | Ballad (民谣体) | 50 | 13 | 63 |
| 4 | `elegy` | Elegy (挽歌) | 49 | 12 | 61 |
| 5 | `free verse` | Free verse (自由诗) | 39 | 10 | 49 |
| 6 | `blank verse` | Blank verse (无韵诗) | 34 | 9 | 43 |
| 7 | `ode` | Ode (颂歌) | 34 | 8 | 42 |
| 8 | `dramatic monologue` | Dramatic monologue (戏剧独白) | 33 | 8 | 41 |
| 9 | `prose poem` | Prose poem (散文诗) | 30 | 8 | 38 |
| 10 | `pastoral` | Pastoral (牧歌) | 29 | 7 | 36 |
| 11 | `haiku` | Haiku (俳句) | 13 | 3 | 16 |
| 12 | `quatrain` | Quatrain (四行) | 10 | 3 | 13 |
| 13 | `ekphrasis` | Ekphrasis (艺格敷词) | 8 | 2 | 10 |
| 14 | `ars poetica` | Ars poetica (诗艺) | 8 | 2 | 10 |
\* totals are class counts after length filtering (same pool used for train/test).
### Dropped forms (count < 10)
| form | count |
|------|------:|
| limerick | 6 |
| concrete or pattern poetry | 5 |
| aubade | 3 |
| sestina | 3 |
| ghazal | 2 |
| villanelle | 1 |
| pantoum | 1 |
## Construction method
1. Load English JSONL from multilingual-annotated-poems.
2. Keep rows with non-empty gold `form` and `text`.
3. Filter by character length; keep classes with frequency ≥ 10.
4. Map forms to contiguous ids (frequency-descending).
5. Stratified train/test split by form (no validation).
## How to load
```python
from datasets import load_dataset
ds = load_dataset("PoetryMTEB/EnglishPoetryFormClassification")
print(ds["test"][0]["label_name"], ds["test"][0]["poem"][:80])
```
## Citation
```bibtex
@misc{riazhsks_multilingual_annotated_poems,
title={Multilingual Annotated Poems},
author={riazhsks},
year={2025},
url={https://github.com/riazhsks/multilingual-annotated-poems}
}
@inproceedings{walsh-etal-2024-sonnet,
title={Sonnet or Not, Bot? Poetry Evaluation for Large Models and Datasets},
author={Walsh, Melanie and Preus, Anna and Antoniak, Maria},
booktitle={Findings of EMNLP 2024},
year={2024},
url={https://aclanthology.org/2024.findings-emnlp.914/}
}
```
Hub packaging: `PoetryMTEB/EnglishPoetryFormClassification` (v1.0.0).
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