Skip to main content

ELFEN - Efficient Linguistic Feature Extraction for Natural Language Datasets

Project description

ELFEN - Efficient Linguistic Feature Extraction for Natural Language Datasets

This python package provides efficient linguistic feature extraction for text datasets (i.e. datasets with N text instances, in a tabular structure).

For further information, check the GitHub repository and the documentation

Using spacy models

If you want to use the spacy backbone, you will need to download the respective model, e.g. "en_core_web_sm":

python -m spacy download en_core_web_sm

Usage of third-party resources usable in this package

The extraction of psycholinguistic, emotion/lexicon and semantic features relies on third-party resources such as lexicons. Please refer to the original author's licenses and conditions for usage, and cite them if you use the resources through this package in your analyses.

For an overview which features use which resource, and how to export all third-party resource references in a bibtex string, consult the documentation.

Acknowledgements

While all feature extraction functions in this package are written from scratch, the choice of features in the readability and lexical richness feature areas (partially) follows the readability and lexicalrichness python packages.

We use the wn python package to extract Open Multilingual Wordnet synsets.

Citation

If you use this package in your work, for now, please cite

@misc{maurer-2025-elfen,
  author = {Maurer, Maximilian},
  title = {ELFEN - Efficient Linguistic Feature Extraction for Natural Language Datasets},
  year = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/mmmaurer/elfen}},
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

elfen-1.1.4.tar.gz (46.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

elfen-1.1.4-py3-none-any.whl (52.5 kB view details)

Uploaded Python 3

File details

Details for the file elfen-1.1.4.tar.gz.

File metadata

  • Download URL: elfen-1.1.4.tar.gz
  • Upload date:
  • Size: 46.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for elfen-1.1.4.tar.gz
Algorithm Hash digest
SHA256 5cf4995618fad5c495b9bffa8a89fab5e1cc0b533d7a3dd8a5a667662c293982
MD5 8a27d3c5f419f96a10895c608f843674
BLAKE2b-256 8af7c70120d8d0817bb1a467beb157a2bba8e1cc643fb8302e79ea1de1f83762

See more details on using hashes here.

File details

Details for the file elfen-1.1.4-py3-none-any.whl.

File metadata

  • Download URL: elfen-1.1.4-py3-none-any.whl
  • Upload date:
  • Size: 52.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for elfen-1.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 ffa6ea8c4bd2e070c159cbac59b69547a544374a6653a4ba4b2d2746edbad0a4
MD5 eb18ae592a6e9e7b9b259444d9155cec
BLAKE2b-256 31a47de741cd35b177a90603935bd8415e6dbd8c2526d63a823abc7c470255ad

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page