gavinxing/amttl

---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- zh
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- parsing
pretty_name: AMTTL
dataset_info:
config_name: amttl
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: tags
sequence:
class_label:
names:
'0': B
'1': I
'2': E
'3': S
splits:
- name: train
num_bytes: 1132196
num_examples: 3063
- name: validation
num_bytes: 324358
num_examples: 822
- name: test
num_bytes: 328509
num_examples: 908
download_size: 274351
dataset_size: 1785063
configs:
- config_name: amttl
data_files:
- split: train
path: amttl/train-*
- split: validation
path: amttl/validation-*
- split: test
path: amttl/test-*
default: true
---

# Dataset Card for AMTTL

## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)

## Dataset Description

- **Homepage:** [Github](https://github.com/adapt-sjtu/AMTTL/tree/master/medical_data)
- **Repository:** [Github](https://github.com/adapt-sjtu/AMTTL/tree/master/medical_data)
- **Paper:** [Aclweb](http://aclweb.org/anthology/C18-1307)
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

[More Information Needed]

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information
```bibtex
@inproceedings{xing2018adaptive,
title={Adaptive multi-task transfer learning for Chinese word segmentation in medical text},
author={Xing, Junjie and Zhu, Kenny and Zhang, Shaodian},
booktitle={Proceedings of the 27th International Conference on Computational Linguistics},
pages={3619--3630},
year={2018}
}
```
### Contributions

Thanks to [@JetRunner](https://github.com/JetRunner) for adding this dataset.

原始信息汇总

数据集概述

• 名称: AMTTL
• 语言: 中文 (zh)
• 许可证: MIT
• 多语言性: 单语种
• 大小: 1K<n<10K
• 来源: 原始数据
• 任务类别: 词元分类
• 任务ID: 解析

数据集结构

• 配置名称: amttl
• 特征:
  • id: 字符串类型
  • tokens: 字符串序列
  • tags: 序列标签，包括 B, I, E, S
• 数据分割:
  • 训练集: 3063个样本，1132196字节
  • 验证集: 822个样本，324358字节
  • 测试集: 908个样本，328509字节
• 下载大小: 274351字节
• 数据集大小: 1785063字节

数据集创建

• 注释创建者: 众包
• 语言创建者: 发现
• 源数据: 原始数据
• 注释: 众包完成

其他信息

• 贡献者: @JetRunner