Skip to main content

Libraries and scripts for DELPH-IN data

Project description

PyDelphin — Python libraries for DELPH-IN data

PyPI Version Python Support Build Status Documentation Status

DELPH-IN is an international consortium of researchers committed to producing precise, high-quality language processing tools and resources, primarily in the HPSG syntactic and MRS semantic frameworks, and PyDelphin is a suite of Python libraries for processing data and interacting with tools in the DELPH-IN ecosystem. PyDelphin's goal is to lower the barriers to making use of DELPH-IN resources to help users quickly build applications or perform experiments, and it has been successfully used for research into machine translation (e.g., Goodman, 2018), sentence chunking (Muszyńska, 2016), neural semantic parsing (Buys & Blunsom, 2017), natural language generation (Hajdik et al., 2019), and more.

Documentation, including guides and an API reference, is available here: http://pydelphin.readthedocs.io/

New to PyDelphin? Want to see examples? Try the walkthrough.

Installation and Upgrading

Get the latest release of PyDelphin from PyPI:

$ pip install pydelphin

For more information about requirements, installing from source, and running unit tests, please see the documentation.

API changes in new versions are documented in the CHANGELOG, but for any unexpected changes please file an issue.

Features

PyDelphin contains the following modules:

Semantic Representations:

Semantic Components and Interfaces:

Grammar and Parse Inspection:

Tokenization:

Corpus Management and Processing:

Interfaces with External Processors:

Core Components and Command Line Interface:

Other Information

Citation

Please use the following for academic citations (and see: https://ieeexplore.ieee.org/abstract/document/8939628):

@INPROCEEDINGS{Goodman:2019,
  author={Goodman, Michael Wayne},
  title={A Python Library for Deep Linguistic Resources},
  booktitle={2019 Pacific Neighborhood Consortium Annual Conference and Joint Meetings (PNC)},
  year={2019},
  month=oct,
  address={Singapore},
  keywords={research software;linguistics;semantics;HPSG;computational linguistics;natural language processing;open source software}
}

Acknowledgments

Thanks to PyDelphin's contributors and all who've participated by filing issues and feature requests. Also thanks to the users of PyDelphin!

Related Software

Spelling

Earlier versions of PyDelphin were spelled "pyDelphin" with a lower-case "p" and this form is used in several publications. The current recommended spelling has an upper-case "P".

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

PyDelphin-1.2.0.tar.gz (140.8 kB view details)

Uploaded Source

Built Distribution

PyDelphin-1.2.0-py3-none-any.whl (171.6 kB view details)

Uploaded Python 3

File details

Details for the file PyDelphin-1.2.0.tar.gz.

File metadata

  • Download URL: PyDelphin-1.2.0.tar.gz
  • Upload date:
  • Size: 140.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.8.0

File hashes

Hashes for PyDelphin-1.2.0.tar.gz
Algorithm Hash digest
SHA256 c8882bb36b98deb3852b702c42249f2d0b0c4f0875493728503a21b872442446
MD5 6149ecc623b69f612ac32a242078017b
BLAKE2b-256 69ddd249ca57d74564a39bd47575ba5d7d91076cc00604ab5aed82cc50bd9124

See more details on using hashes here.

File details

Details for the file PyDelphin-1.2.0-py3-none-any.whl.

File metadata

  • Download URL: PyDelphin-1.2.0-py3-none-any.whl
  • Upload date:
  • Size: 171.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.8.0

File hashes

Hashes for PyDelphin-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 19d9d49c3dc711835a61e1028bc5a982104ea5932ee4809d1d1319a6799860b9
MD5 866c24e586d691ebbd8067eae4e8b0a4
BLAKE2b-256 2d083618b8ebe31609e4e70f2824dc676acf849cb4964201f4b709138ef2d689

See more details on using hashes here.

Supported by

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