relation-extraction | 中文关系抽取 | Natural Language Processing library
kandi X-RAY | relation-extraction Summary
kandi X-RAY | relation-extraction Summary
relation-extraction is a Python library typically used in Artificial Intelligence, Natural Language Processing, Pytorch applications. relation-extraction has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
中文关系抽取
中文关系抽取
Support
Quality
Security
License
Reuse
Support
relation-extraction has a low active ecosystem.
It has 303 star(s) with 43 fork(s). There are 8 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 10 have been closed. On average issues are closed in 11 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of relation-extraction is current.
Quality
relation-extraction has 0 bugs and 0 code smells.
Security
relation-extraction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
relation-extraction code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
relation-extraction is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
relation-extraction releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
relation-extraction saves you 185 person hours of effort in developing the same functionality from scratch.
It has 456 lines of code, 23 functions and 9 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed relation-extraction and discovered the below as its top functions. This is intended to give you an instant insight into relation-extraction implemented functionality, and help decide if they suit your requirements.
- Train model
- Get a dictionary of tag names
- Loads checkpoint from file
- Save checkpoint dictionary to file
- Provide prediction
- Tokenize a single item
- Convert e_pos to a mask
- Split data into training and validation data
- Convert a single line to a dict
- Save data to file
- Forward computation
- Calculate the entity average
- Read data from a tqdm file
Get all kandi verified functions for this library.
relation-extraction Key Features
No Key Features are available at this moment for relation-extraction.
relation-extraction Examples and Code Snippets
No Code Snippets are available at this moment for relation-extraction.
Community Discussions
Trending Discussions on relation-extraction
QUESTION
ConllReader (Like RothCONLL04Reader) throws exception while reading relation training data with custom NER and custom relation
Asked 2017-May-14 at 13:27
In continuation of the following question. How to generate custom training data for Stanford relation extraction
Thanks to StanfordNLPHelp i am able to generate relation data with custom ner and on top of it regexner.
...ANSWER
Answered 2017-May-13 at 14:52The exception was thrown due to extra line break in between. There has to be exactly two line breaks in the input tagged training data like below.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install relation-extraction
You can download it from GitHub.
You can use relation-extraction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use relation-extraction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
