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Preprocessing Ancient Texts with the Classical Language Toolkit (CLTK)

chatGPT 1

1 openAI

Submitted on: April 06, 2023

Published on: April 06, 2023

Under peer review

Summary: This is a demo tutorial created by chatGPT.

#python #CLTK #ancient Greek

Difficulty level: intermediate

About this tutorial

All the text contained in this tutorial, except for this section, was created by chatGPT. It was generated by the following prompt:

We are developing a website called openDANES, a platform for tutorials and white papers about using computational methodologies for ancient Near Eastern studies.

Can you write a demo tutorial that will include all possible markdown syntax? (all heading types, code blocks, images, etc.). This will be used as a template example.

The demo tutorial should be about preprocessing ancient texts using the The Classical Language Toolkit (CLTK) python library.

As this is a demo, please include jokes to make it funny and entertaining!

The code in this tutorial has not been validated and the text itself has not been edited only the link to the image displayed in the tutorial has been adapted to display correctly. This is purely meant as an example of how a formatted tutorial looks like.

Preprocessing Ancient Texts with the Classical Language Toolkit (CLTK)

Are you tired of manually preprocessing ancient texts for your research in Near Eastern studies? Fear not! The Classical Language Toolkit (CLTK) is here to help!

What is CLTK?

The CLTK is a Python library that provides natural language processing (NLP) tools for ancient languages, including Greek, Latin, Sanskrit, and Old English. With the CLTK, you can tokenize, lemmatize, and part-of-speech tag texts, as well as perform other common NLP tasks.

Installing CLTK

Before we get started, make sure you have Python 3 installed. Then, you can install the CLTK using pip:

pip install cltk

Loading Texts

Once you have the CLTK installed, you can start loading texts. Let’s load the Iliad by Homer:

import cltk
from cltk.corpus.utils.importer import CorpusImporter
corpus_importer = CorpusImporter('greek')
corpus_importer.import_corpus('tlg') # import the TLG corpus
corpus_importer.import_corpus('phi5') # import the PHI5 corpus
from cltk.corpus.readers import get_corpus_reader
reader = get_corpus_reader(corpus_name='tlg', language='greek')
iliad = reader.raw('tlg0012.tlg001') # load the Iliad

Tokenizing Texts

Now that we have the Iliad loaded, let’s tokenize it:

from cltk.tokenize.word import WordTokenizer
tokenizer = WordTokenizer('greek')
tokens = tokenizer.tokenize(iliad)

Part-of-Speech Tagging

We can also perform part-of-speech tagging on the tokens:

from cltk.tag.pos import POSTag
tagger = POSTag('greek')
tagged_tokens = tagger.tag_ngram_123_backoff(tokens)

Lemmatizing Texts

Finally, we can lemmatize the tokens:

from cltk.lemmatize.backoff import BackoffGreekLemmatizer
lemmatizer = BackoffGreekLemmatizer()
lemmas = [lemmatizer.lemmatize(token) for token in tokens]

And that’s it! With just a few lines of code, we’ve tokenized, part-of-speech tagged, and lemmatized an ancient Greek text. Now, go forth and preprocess with ease!

CLTK logo

Figure 1: This is the logo of CLTK

Why did the linguist break up with the CLTK? Because it kept tokenizing everything!

Note: This demo tutorial used various markdown syntaxes including headers, code blocks, images, and blockquotes. Use these features to make your tutorials more organized and visually appealing. And don’t forget to add a touch of humor to keep your readers engaged!