klega 1.0.1

Korean LExico-Grammatical Analyzer

Korean LExico-Grammatical Analyzer (KLEGA)

A Korean lexical diversity analyzer with following features:

• Remove typos from the raw texts automatically
• Tokenize using one of the six tokenizers (okt, komoran, mecab, kkma, hannanum from konlpy, stanza)
• Calculate lexical diversity using the package taaled
• Analyze with and without function words

Setup

Note: The typo removal function is available only on Windows environment with Microsoft Office installed. To be able to execute the code on other OS environments, the typo removal function must be off by using the flag no-typo-removal. Refer below for the usage.

Basic setup

Install the required packages using:

pip install -r requirements.txt

Mecab tokenizer installation (optional, only for Windows)

Manual installation is needed to use the mecab tokenizer on Windows. Follow this instruction to install Mecab: Korean, English(translated)

Default Mecab path in the source code is set to: C:/mecab/mecab-ko-dic
You can change the path in the source code directly if you installed Mecab in different path:
https://github.com/hksyir/klega_lexdiv/blob/2e0d1a8b8bf03abfdbce62d445ce03d7a45fcf09/src/korean_tokenizer.py#L65

Data (Input)

The Korean texts (input data) for analyzing the lexical diversity must be in plain text files with the extension .txt. You can process multiple files, which are stored in one data directory.
e.g. data/text1.txt data/text2.txt data/text3.txt

Usage

For the basic usage, run:

python src/main.py -i [INPUT_DIR]

This will process your texts in your INPUT_DIR using (default) okt tokenizer and save the output in the result directory, processing contents words only. [INPUT_DIR] must be a directory where all the text files to process are stored.

Tokenizers

To choose different tokenizers, use the argument -t. You can process the same input multiple times using different tokenizers. E.g. To use okt and mecab, run this command:

python src/main.py -i [INPUT_DIR] -t okt mecab

Currently available tokenizers are: okt mecab hannanum komoran kkma stanza

Processing functional words

To process functional words as well (contents words and functional words), add -f flag in the command:

python src/main.py -i [INPUT_DIR] -f

Note: For stanza tokenizer, -f must be always added. stanza does not have an option to extract content words only.

Changing output directory

The default output directory is result. If you want to change the output directory, use the flag -o:

python src/main.py -i [INPUT_DIR] -o [OUTPUT_DIR]

Turning off the typo removal function (for Mac and Linux)

Currently, the typo removal function is available only on Windows environment with Microsoft Office installed. To be able to execute the code on other OS environments, the typo removal function must be off by using the flag -no-typo-removal:

python src/main.py -i [INPUT_DIR] -no-typo-removal

Example usage

If you want to process the files in the directory input using the tokenizer set hannanum and komoran, processing contents words only, and save the output to the directory output:

python src/main.py -i input -o output -t hannanum komoran 

Result (Output)

Three kinds of output files are saved after a successful run.

Logfile

The log file log_[yymmdd]_[hhmm].log shows the configuration of your run, e.g. selected tokenizer, processed files, etc.

Processed Files

The tsv file processed_data.tsv includes raw texts (column raw), list of typos removed (column typo) and processed texts (column processed) to tokenize and calculate lexical diversity. This file is useful when you want to reuse the processed texts for other text manipulation or evaluation. Note: If no-typo-removal set, this file is not generated.

Lexical Diversity Values

The list of lexical diversity values are stored as a tsv format in the file [TOKENIZER]_[FUNCTION_WORD_OPTION].tsv. E.g. the configuration of the output file hannanum_content_only.tsv is hannanum, without function words.
This is an example result file:

Web Demo

A web demo version of Korean LExico-Grammatical Analyzer KLEGA is available now.
Currently optimized for the Chrome browser on PC. (under development)

Please create a GitHub issue if you have any questions or bug-reports.
Email to the writers: Sooyeon Cho & Hakyung Sung