Relation-extraction | 关系抽取个人实战总结以及开源工具包使用

by FuYanzhe2 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Relation-extraction Summary

Relation-extraction is a Python library. Relation-extraction has no bugs, it has no vulnerabilities and it has low support. However Relation-extraction build file is not available. You can download it from GitHub.

关系抽取个人实战总结以及开源工具包使用

Support

Quality

Security

License

Reuse

Support

Relation-extraction has a low active ecosystem.

It has 50 star(s) with 13 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 0 have been closed. On average issues are closed in 403 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 27 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 2 security hotspots that need review.

License

Relation-extraction does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Relation-extraction releases are not available. You will need to build from source code and install.

Relation-extraction has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Relation-extraction saves you 314 person hours of effort in developing the same functionality from scratch.

It has 754 lines of code, 43 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.

Builds inputs
Load raw data from file
Map the words to the ID
Build a vocabulary
Run one epoch
Convert a dataset to sentence ids
Embed a relative position
Loads an embedding matrix
Run the model
Create a feed dictionary for training
Load data from file
Evaluate the prediction
Builds the word vocab
Iterate batch data

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

ConllReader (Like RothCONLL04Reader) throws exception while reading relation training data with custom NER and custom relation

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 14:52

The 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.

Source https://stackoverflow.com/questions/43932872

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.

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 .

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