---
task_categories:
- token-classification
language:
- vi
---
## Dataset Card for BKEE

### 1. Dataset Summary

**BKEE** is the first Vietnamese **Event Extraction** dataset, containing **1,066** fully annotated documents covering:

* **33+ event types**
* **28 argument roles**
* Entity mentions, event mentions, and relation mentions

This resource addresses the lack of Vietnamese‑specific EE datasets and supports tasks from event detection to argument extraction.


### 2. Supported Tasks and Metrics

* **Tasks**

  * Entity Mention Detection
  * Event Detection
  * Event Argument Extraction
* **Metrics**

  * Precision / Recall / F1 (per subtask)
  * Overall document‑level accuracy


### 3. Languages

* Vietnamese

### 4. Dataset Structure

All splits have been merged into one CSV. Each row corresponds to one sentence mention:

| Column              | Type   | Description                                           |
| ------------------- | ------ | ----------------------------------------------------- |
| `doc_id`            | string | Unique document identifier (e.g. “train-00001”).      |
| `sent_id`           | string | Unique sentence identifier within a document.         |
| `tokens`            | list   | Tokenized words.                                      |
| `sentence`          | string | Original sentence text.                               |
| `event_types`       | list   | List of event type labels occurring in this sentence. |
| `argument_roles`    | list   | List of argument-role labels aligned to `tokens`.     |
| `entity_mentions`   | list   | List of entity mention spans (start, end, label).     |
| `event_mentions`    | list   | List of event trigger spans (start, end, label).      |
| `relation_mentions` | list   | List of relations between arguments and events.       |
| `type`              | string | Split: `train` / `dev` / `test`.               |
| `dataset`           | string | Always `BKEE` (for provenance).                       |


### 5. Data Fields

* **doc\_id**, **sent\_id** (`str`): Document and sentence IDs.
* **tokens** (`List[str]`): Tokenized text.
* **sentence** (`str`): Raw sentence.
* **event\_types**, **argument\_roles**, **entity\_mentions**, **event\_mentions**, **relation\_mentions**: Annotations per sentence.
* **type** (`str`): Data split.
* **dataset** (`str`): Always `BKEE`.


### 6. Usage

```python
from datasets import load_dataset

ds = load_dataset("visolex/BKEE")

# Filter by split
train = ds.filter(lambda ex: ex["type"] == "train")
val   = ds.filter(lambda ex: ex["type"] == "dev")
test  = ds.filter(lambda ex: ex["type"] == "test")

# Inspect one example
print(train[0])
```


### 7. Source & Links

* **GitHub** (original data & code):
  [https://github.com/nhungnt/BKEE](https://github.com/nhungnt/BKEE) ([github.com][2])
* **Paper**:
  Thi‑Nhung Nguyen et al. (2024), “BKEE: Pioneering Event Extraction in the Vietnamese Language,” *LREC‑COLING 2024*. ([aclanthology.org][1])
* **Hugging Face (this unified version)**:
  [https://huggingface.co/datasets/visolex/BKEE](https://huggingface.co/datasets/visolex/BKEE)


### 8. License

Released under **CC BY‑NC 4.0**. See the GitHub repo for full terms.


### 9. Citation

```bibtex
@inproceedings{nguyen-etal-2024-bkee,
  title     = {BKEE: Pioneering Event Extraction in the Vietnamese Language},
  author    = {Nguyen, Thi-Nhung and Tran, Bang Tien and Luu, Trong-Nghia and 
               Nguyen, Thien Huu and Nguyen, Kiem-Hieu},
  booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
  month     = may,
  year      = {2024},
  address   = {Torino, Italia},
  publisher = {ELRA and ICCL},
  url       = {https://aclanthology.org/2024.lrec-main.217},
  pages     = {2421--2427}
}
```

```bibtex
@misc{nhungnt_bkee,
  title        = {BKEE: Pioneering Event Extraction in the Vietnamese Language},
  author       = {{nhungnt}},
  howpublished = {\url{https://github.com/nhungnt/BKEE}},
  year         = {2024}
}
```