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---
task_categories:
- token-classification
language:
- vi
---
## Dataset Card for ViLexNorm
### 1. Dataset Summary
**ViLexNorm** is a Vietnamese lexical normalization corpus of **10,467** comment pairs, each comprising an *original* noisy social‑media comment and its *normalized* counterpart. In this unified version, all pairs are merged into one CSV with a `type` column indicating `train` / `dev` / `test`, and two additional columns `input`/`output` containing the tokenized forms.
### 2. Supported Tasks and Metrics
* **Primary Task**: Sequence‑to‑sequence lexical normalization
* **Metric**:
* **Error Reduction Rate (ERR)** (van der Goot 2019)
* **Token‑level accuracy**
### 3. Languages
* Vietnamese
### 4. Dataset Structure
| Column | Type | Description |
| ------------ | ------ | -------------------------------------------- |
| `original` | string | The raw, unnormalized comment. |
| `normalized` | string | The corrected, normalized comment. |
| `input` | list | Tokenized original text (list of strings). |
| `output` | list | Tokenized normalized text (list of strings). |
| `type` | string | Split: `train` / `validation` / `test`. |
| `dataset` | string | Always `ViLexNorm` for provenance. |
### 5. Data Fields
* **original** (`str`): Noisy input sentence.
* **normalized** (`str`): Human‑annotated normalized sentence.
* **input** (`List[str]`): Token list of `original`.
* **output** (`List[str]`): Token list of `normalized`.
* **type** (`str`): Which split the example belongs to.
* **dataset** (`str`): Always `ViLexNorm`.
### 6. Usage
```python
from datasets import load_dataset
ds = load_dataset("visolex/ViLexNorm")
train = ds.filter(lambda ex: ex["type"] == "train")
val = ds.filter(lambda ex: ex["type"] == "dev")
test = ds.filter(lambda ex: ex["type"] == "test")
print(train[0])
```
### 7. Source & Links
* **Paper**: Nguyen et al. (2024), “ViLexNorm: A Lexical Normalization Corpus for Vietnamese Social Media Text”
[https://aclanthology.org/2024.eacl-long.85](https://aclanthology.org/2024.eacl-long.85)
* **Hugging Face** (this unified version):
[https://huggingface.co/datasets/visolex/ViLexNorm](https://huggingface.co/datasets/visolex/ViLexNorm)
* **Original GitHub** (if available):
[https://github.com/ngxtnhi/ViLexNorm](https://github.com/ngxtnhi/ViLexNorm)
### 8. Contact Information
* **Ms. Thanh‑Nhi Nguyen**: [21521232@gm.uit.edu.vn](mailto:21521232@gm.uit.edu.vn)
* **Mr. Thanh‑Phong Le**: [21520395@gm.uit.edu.vn](mailto:21520395@gm.uit.edu.vn)
### 9. Licensing and Citation
#### License
Released under **CC BY‑NC‑SA 4.0** (Creative Commons Attribution‑NonCommercial‑ShareAlike 4.0 International).
#### How to Cite
```bibtex
@inproceedings{nguyen-etal-2024-vilexnorm,
title = {ViLexNorm: A Lexical Normalization Corpus for Vietnamese Social Media Text},
author = {Nguyen, Thanh-Nhi and Le, Thanh-Phong and Nguyen, Kiet},
booktitle = {Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
month = mar,
year = {2024},
address = {St. Julian's, Malta},
publisher = {Association for Computational Linguistics},
url = {https://aclanthology.org/2024.eacl-long.85},
pages = {1421--1437}
}
``` |