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https://github.com/alexeyev/ruconceptnet

/ru/ConceptNet5.7 Python wrapper

https://github.com/alexeyev/ruconceptnet

Science Score: 13.0%

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Keywords

conceptnet knowledge-graph russian-language russian-nlp
Last synced: 6 months ago · JSON representation

Repository

/ru/ConceptNet5.7 Python wrapper

Basic Info
  • Host: GitHub
  • Owner: alexeyev
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 4.11 MB
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conceptnet knowledge-graph russian-language russian-nlp
Created over 5 years ago · Last pushed about 5 years ago
Metadata Files
Readme License

README.md

/ru/ConceptNet

ConceptNet 5.7 (Russian part) extraction scripts + fast API object to access the relations. Note: a simple modification of the preprocessing script allows to build a queryable graph of any other subset of ConceptNet.

Python 3x PyPI version Downloads

Installation

pip install ruconceptnet

Usage

```

from ruconceptnet import ConceptNet cn = ConceptNet() cn.gettargets("алкоголь") [('этиловыйспирт', {'Synonym'}), ('спиртной_напиток', {'Synonym'}), ('алкогольный', {'RelatedTo'}), ('алкоголик', {'RelatedTo'}), ('спирт', {'Synonym'}), ('алкоголизация', {'RelatedTo'})]

cn.get_sources("йога") [('йоги', {'FormOf'}), ('йогу', {'FormOf'}), ('йогический', {'RelatedTo'}), ('йогою', {'FormOf'}), ('йогой', {'FormOf'}), ('йог', {'RelatedTo'}), ('йоге', {'FormOf'})]

cn.check_pair("человек", "зверь") (['DistinctFrom'], [])

cn.check_pair("зверь", "человек") ([], ['DistinctFrom']) ```

Preparations for customization

Please see the prepare_data.sh script. We get the Russian-Russian pairs of nodes with simple grep and build a 3-dimensional array (source, target, relation) stored as a single sparse SciPy matrix.

Citing

Please do not forget to cite the ConceptNet5 paper. @inproceedings{10.5555/3298023.3298212, author = {Speer, Robyn and Chin, Joshua and Havasi, Catherine}, title = {ConceptNet 5.5: An Open Multilingual Graph of General Knowledge}, year = {2017}, publisher = {AAAI Press}, booktitle = {Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence}, pages = {4444–4451}, numpages = {8}, location = {San Francisco, California, USA}, series = {AAAI'17} }

Citing the repository is not necessary, but greatly appreciated as well, if you use this work.

@misc{ruconceptnet2020alekseev, title = {{alexeyev/RuConceptNet: /ru/ConceptNet5.7 Python wrapper }}, year = {2020}, url = {https://github.com/alexeyev/RuConceptNet}, language = {english} }

License

The code is released under the MIT license (please see the LICENSE file).

This work includes a subset data from ConceptNet 5, which was compiled by the Commonsense Computing Initiative. ConceptNet 5 is freely available under the Creative Commons Attribution-ShareAlike license (CC BY SA 3.0) from http://conceptnet.io.

The included data was created by contributors to Commonsense Computing projects, contributors to Wikimedia projects, DBPedia, OpenCyc, Games with a Purpose, Princeton University's WordNet, Francis Bond's Open Multilingual WordNet, and Jim Breen's JMDict.

The complete data in ConceptNet is available under the Creative Commons Attribution-ShareAlike 4.0 license.

For more details, please see "Copying and sharing ConceptNet".

Owner

  • Name: Anton Alekseev
  • Login: alexeyev
  • Kind: user

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Dependencies

requirements.txt pypi
  • pandas >=1.1.4
  • scipy >=1.5.4