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 variationfrom 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:
See MulDi Chinese manual.pdf for more details
The manual contains a detailed description of the 60 features.
1 maintainer
Metadata
1 maintainer
Release files for muldichinese 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| muldichinese-0.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Release files / muldichinese-0.3.2-py3-none-any.whl
| Download URL | muldichinese-0.3.2-py3-none-any.whl |
|---|---|
| Size | 48.8 kB |
| Tags | Python 3 |
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