/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.

Installation

pip install ruconceptnet

Usage

>>> from ruconceptnet import ConceptNet
>>> cn = ConceptNet()
>>> cn.get_targets("алкоголь")
[('этиловый_спирт', {'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”.