语法错误数据增强
针对行业语法错误数据稀缺问题,提出语法错误替换方法,可以根据领域的数据进行语法错误制作,定制化行业模型。
目前支持缺字漏字、错别字错误、缺少标点、错用标点、主语不明、谓语残缺、宾语残缺、其他成分残缺、主语多余、虚词多余、其他成分多余、语序不当、动宾搭配不当、其他搭配不当等14种细粒度错误类型的替换。如下图所示:
也可以对一个句子进行多种错误的替换,如下:
模型文件下载
pre_model下的ltp_small,下载地址:https://huggingface.co/LTP/small
获得2024CCL Task7 一等奖
2024CCL Task7: https://github.com/cubenlp/2024CCL_CEFE
博客经验分享:https://www.cnblogs.com/twnlp/p/18208637
评测论文:待发表
Metadata
Release files for GrammarEnhancer 1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| grammarenhancer-1.1.tar.gz | 7.6 kB | Without provenance | Details for grammarenhancer-1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| GrammarEnhancer-1.1-py3-none-any.whl | Python 3 | none | any | Details for GrammarEnhancer-1.1-py3-none-any.whl |
Total release size: 15.3 kB
Release files / grammarenhancer-1.1.tar.gz
| Download URL | grammarenhancer-1.1.tar.gz |
|---|---|
| Size | 7.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c5e0a03a7dfa07dfa20a53835ea8c08d44b429fb6795c0b540f1b963c40501bf
|
|
BLAKE2b-256 checksum How to use checksums |
76d5cbf074521653063632cc57bb86e704626ac6000e02d294118e5e2ff94310
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.8.19
|
Release files / GrammarEnhancer-1.1-py3-none-any.whl
| Download URL | GrammarEnhancer-1.1-py3-none-any.whl |
|---|---|
| Size | 7.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c71be35bb06e74effce511b7b6635ee8941b6eba2a2b5a2e599001cdf28385e1
|
|
BLAKE2b-256 checksum How to use checksums |
bc7902e31530f675c31ba79ea367b129204c7a94bfc20535fc9f6c0ef87a7682
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.8.19
|
Security for GrammarEnhancer 1.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.