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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,93 +1,95 @@ | ||
| [](https://pypi.org/project/ltp/) | ||
|  | ||
|  | ||
|  | ||
|  | ||
| [](https://ltp.readthedocs.io/zh_CN/latest/?badge=latest) | ||
| [](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)** | ||
|
|
||
| ## Language Bindings | ||
|
|
||
| + C++ | ||
| + Rust | ||
| + Java | ||
| + Python Rebinding | ||
|
|
||
| [libltp](https://github.com/HIT-SCIR/libltp) | ||
|
|
||
| ## 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 <<[[email protected]](mailto:[email protected])>> | ||
|
|
||
| ## 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 [email protected] 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[email protected]，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) | ||
| [](https://pypi.org/project/ltp/) | ||
|  | ||
|  | ||
|  | ||
|  | ||
| [](https://ltp.readthedocs.io/zh_CN/latest/?badge=latest) | ||
| [](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)** | ||
|
|
||
| ## Language Bindings | ||
|
|
||
| + C++ | ||
| + Rust | ||
| + Java | ||
| + Python Rebinding | ||
|
|
||
| [libltp](https://github.com/HIT-SCIR/libltp) | ||
|
|
||
| ## 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 | 39.12 | | ||
| | LTP 4.0 (Base1) | 99.22 | 98.73 | 96.39 | 79.28 | 89.57 | 76.57 | --.-- | | ||
| | LTP 4.0 (Base2) | 99.18 | 98.69 | 95.97 | 79.49 | 90.19 | 76.62 | --.-- | | ||
| | LTP 4.0 (Small) | 98.4 | 98.2 | 94.3 | 78.4 | 88.3 | 74.7 | 43.13 | | ||
| | LTP 4.0 (Tiny) | 96.8 | 97.1 | 91.6 | 70.9 | 83.8 | 70.1 | 53.22 | | ||
|
|
||
| **[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 <<[[email protected]](mailto:[email protected])>> | ||
|
|
||
| ## 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 [email protected] 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[email protected]，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) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
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