Skip to main content

A Chinese register analyser.

Project description

Multidimensional-Analysis-Tagger-of-Mandarin-Chinese

MulDi Chinese (IPA: [ˌmʌl'daɪ] [ˌtʃaɪˈniːz]) is a multidimensional analysis tagger of Mandarin Chinese.

  • Installation: pip install muldichinese

About

Check the names of your input files, segment and pos tag the texts, and get the distribution of linguistic features and dimension scores of register variation
from muldichinese import MulDiChinese
mdc=MulDiChinese('/write/path/to/your/file(s)/')
mdc.files()
mdc.pos()
Segmentation and pos tagging completed.
mdc.features()
Standardised frequencies of all 60 features written.
mdc.dimensions()
Dimension scores written.

Reference the tagger

Liu, N. 2019. Multidimensional Analysis Tagger of Mandarin Chinese. Available at: https://github.com/Nannan-Liu/Multidimensional-Analysis-Tagger-of-Mandarin-Chinese.

This programme is based on the ICTCLAS, and it is advised to reference ICTCLAS when MulDi Chinese is used. Please refer to https://dl.acm.org/citation.cfm?id=1119280.

Requirements

Python packages needed are:

  1. PyNLPIR
  2. NLTK
  3. Pandas
  4. scikit learn
  5. NumPy

See MulDi Chinese manual.pdf for more details

The manual contains a detailed description of the 60 features.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

muldichinese-0.3.2-py3-none-any.whl (48.8 kB view details)

Uploaded Python 3

File details

Details for the file muldichinese-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: muldichinese-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 48.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.6.1 requests/2.25.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.9.0

File hashes

Hashes for muldichinese-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 fc60b799721e5bd45846284c3b4832470ff0271e0d950e951d6072bc2a93ae6a
MD5 414942a83fe3386a3c5c926921f75a81
BLAKE2b-256 b88650521a4dc58b969d3ca1e07b5ff76ea0159839b73cff951fb55bacb53f88

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