SubGTR | Temporal Knowledge Graph Question Answering via Subgraph Reasoning

by czy1999 Python Version: Current License: No License

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

kandi X-RAY | SubGTR Summary

SubGTR is a Python library. SubGTR has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

This is the code for the manuscript "Temporal Knowledge Graph Question Answering via Subgraph Reasoning" (KBS). Paper:

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Quality

Security

License

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Support

SubGTR has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SubGTR is current.

Quality

SubGTR has no bugs reported.

Security

SubGTR has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

SubGTR 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

SubGTR 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, examples and code snippets are available.

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SubGTR Key Features

No Key Features are available at this moment for SubGTR.

SubGTR Examples and Code Snippets

No Code Snippets are available at this moment for SubGTR.

Community Discussions

No Community Discussions are available at this moment for SubGTR.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install SubGTR

Clone and create a conda environment. The implementation is based on TempoQR in TempoQR: Temporal Question Reasoning over Knowledge Graphs and their code from https://github.com/cmavro/TempoQR. You can find more installation details there. We use TComplEx KG Embeddings as implemented in https://github.com/facebookresearch/tkbc.

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: