参考：
amttl
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:amttl/amttl')
- 说明：
Chinese word segmentation (CWS) trained from open source corpus faces dramatic performance drop
when dealing with domain text, especially for a domain with lots of special terms and diverse
writing styles, such as the biomedical domain. However, building domain-specific CWS requires
extremely high annotation cost. In this paper, we propose an approach by exploiting domain-invariant
knowledge from high resource to low resource domains. Extensive experiments show that our mode
achieves consistently higher accuracy than the single-task CWS and other transfer learning
baselines, especially when there is a large disparity between source and target domains.
This dataset is the accompanied medical Chinese word segmentation (CWS) dataset.
The tags are in BIES scheme.
For more details see https://www.aclweb.org/anthology/C18-1307/
- 许可：无已知许可
- 版本：1.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
908 |
'train' |
3063 |
'validation' |
822 |
- 特征：
{
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"_type": "Value"
},
"tokens": {
"feature": {
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},
"length": -1,
"id": null,
"_type": "Sequence"
},
"tags": {
"feature": {
"num_classes": 4,
"names": [
"B",
"I",
"E",
"S"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
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}
}