Metadata-Version: 2.1
Name: ltp
Version: 4.1.1
Summary: Language Technology Platform
Home-page: https://github.com/HIT-SCIR/ltp
Author: Yunlong Feng
Author-email: ylfeng@ir.hit.edu.cn
License: UNKNOWN
Description: [![LTP](https://img.shields.io/pypi/v/ltp?label=LTP4%20ALPHA)](https://pypi.org/project/ltp/)
        ![VERSION](https://img.shields.io/pypi/pyversions/ltp)
        ![CODE SIZE](https://img.shields.io/github/languages/code-size/HIT-SCIR/ltp)
        ![CONTRIBUTORS](https://img.shields.io/github/contributors/HIT-SCIR/ltp)
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        [![Documentation Status](https://readthedocs.org/projects/ltp/badge/?version=latest)](https://ltp.readthedocs.io/zh_CN/latest/?badge=latest)
        [![PyPI Downloads](https://img.shields.io/pypi/dm/ltp)](https://pypi.python.org/pypi/ltp)
        
        # LTP 4 
        
        LTP（Language Technology Platform） 提供了一系列中文自然语言处理工具，用户可以使用这些工具对于中文文本进行分词、词性标注、句法分析等等工作。
        
        If you use any source codes included in this toolkit in your work, please kindly cite the following paper. The bibtex are listed below:
        <pre>
        @article{che2020n,
          title={N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models},
          author={Che, Wanxiang and Feng, Yunlong and Qin, Libo and Liu, Ting},
          journal={arXiv preprint arXiv:2009.11616},
          year={2020}
        }
        </pre>
        
        ## 快速使用
        
        ```python
        from ltp import LTP
        ltp = LTP() # 默认加载 Small 模型
        seg, hidden = ltp.seg(["他叫汤姆去拿外衣。"])
        pos = ltp.pos(hidden)
        ner = ltp.ner(hidden)
        srl = ltp.srl(hidden)
        dep = ltp.dep(hidden)
        sdp = ltp.sdp(hidden)
        ```
        
        **[详细说明](docs/quickstart.rst)**
        
        ## 指标
        
        |      模型       | 分词  | 词性  | 命名实体 | 语义角色 | 依存句法 | 语义依存 | 速度(句/S) |
        | :-------------: | :---: | :---: | :------: | :------: | :------: | :------: | :--------: |
        | LTP 4.0 (Base)  | 98.7  | 98.5  |   95.4   |   80.6   |   89.5   |   75.2   |            |
        | LTP 4.0 (Small) | 98.4  | 98.2  |   94.3   |   78.4   |   88.3   |   74.7   |   12.58    |
        | LTP 4.0 (Tiny)  | 96.8  | 97.1  |   91.6   |   70.9   |   83.8   |   70.1   |   29.53    |
        
        **[模型下载地址](MODELS.md)**
        
        ## 模型算法
        
        + 分词: Electra Small<sup>[1](#RELTRANS)</sup> + Linear
        + 词性: Electra Small + Linear
        + 命名实体: Electra Small + Relative Transformer<sup>[2](#RELTRANS)</sup> + Linear
        + 依存句法: Electra Small + BiAffine + Eisner<sup>[3](#Eisner)</sup>
        + 语义依存: Electra Small + BiAffine
        + 语义角色: Electra Small + BiAffine + CRF
        
        ## 构建 Wheel 包
        
        ```shell script
        python setup.py sdist bdist_wheel
        python -m twine upload dist/*
        ```
        
        ## 作者信息
        
        + 冯云龙 <<[ylfeng@ir.hit.edu.cn](mailto:ylfeng@ir.hit.edu.cn)>>
        
        ## 开源协议
        1. 语言技术平台面向国内外大学、中科院各研究所以及个人研究者免费开放源代码，但如上述机构和个人将该平台用于商业目的（如企业合作项目等）则需要付费。
        2. 除上述机构以外的企事业单位，如申请使用该平台，需付费。
        3. 凡涉及付费问题，请发邮件到 car@ir.hit.edu.cn 洽商。
        4. 如果您在 LTP 基础上发表论文或取得科研成果，请您在发表论文和申报成果时声明“使用了哈工大社会计算与信息检索研究中心研制的语言技术平台（LTP）”. 同时，发信给car@ir.hit.edu.cn，说明发表论文或申报成果的题目、出处等。
        
        
        ## 脚注
        
        + <a name="RELTRANS">1</a>:: [Chinese-ELECTRA](https://github.com/ymcui/Chinese-ELECTRA)
        + <a name="RELTRANS">2</a>:: [TENER: Adapting Transformer Encoder for Named Entity Recognition](https://arxiv.org/abs/1911.04474)
        + <a name="Eisner">3</a>:: [A PyTorch implementation of "Deep Biaffine Attention for Neural Dependency Parsing"](https://github.com/yzhangcs/parser)
        
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries
Requires-Python: >=3.6.*, <4
Description-Content-Type: text/markdown
