Metadata-Version: 2.1
Name: getcl
Version: 0.1
Summary: Python Package for the Mapping of Conceptlists
Home-page: https://github.com/lingpy/getcl/
Author: Johann-Mattis List
Author-email: mattis.list@uni-passau.de
License: MIT
Keywords: word prediction
Platform: any
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pysem >=0.5.0
Requires-Dist: pyconcepticon
Requires-Dist: cldfbench
Requires-Dist: tabulate
Requires-Dist: clldutils
Requires-Dist: pycldf
Provides-Extra: dev
Requires-Dist: wheel ; extra == 'dev'
Requires-Dist: twine ; extra == 'dev'
Provides-Extra: test
Requires-Dist: pytest >=4.3 ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Requires-Dist: coverage >=4.2 ; extra == 'test'

# `getcl`: Mapping Lexical Data from CLDF Dictionaries to Wordlists

`getcl` offers the code for mapping lexical data from a CLDF dictionary to a wordlist as described in the following paper:

> Blum, Frederic and Englisch, Johannes and Hermida Rodriguez, Alba and van Gijn, Rik and List, Johann-Mattis (2024). To be published in the Proceedings of the 2nd Meeting of the ELRA/ISCA Special Interest Group on Under-Resourced Languages.

To install the tool, just clone this repository and then type:

```
pip install -e .
```

This will provide a new command `conceptlist` that you can use to map concepts in the sense descriptions of a dictionary to Concepticon.

To test the package, you can just run the following code:

```
$ git clone https://github.com/dictionaria/kalamang.git
$ conceptlist --data kalamang/cldf/cldf-metadata.json --conceptlist Swadesh-1955-100 --output kalamang.tsv | wc -l
```
The output should be 197. This means that 196 matches for the 100 concepts of Swadesh's concept list could be identified. To get a useful concept list of these matches (that contain duplicates and potential errors), you would not look at the file `kalamang.tsv` and modify it manually to arrive at a Swadesh list derived from the dictionary.
