NLP_LAT_COLL

A Natural Language Processing collection for Latin texts, featuring the Satyricon corpus with tokenized data and XML markup.

Overview

This project contains annotated Latin text data from the Satyricon by Petronius, processed for computational linguistic analysis. The collection includes both complete and selected text versions with corresponding tokenized data and schema definitions.

Contents

• SatyriconFullText.txt - Complete text of the Satyricon
• SatyriconSelectedText.txt - Curated selection of Satyricon excerpts
• corpus_sermo_vulgaris.xml - XML-formatted corpus with linguistic annotations
• corpus_sermo_vulgaris_token.csv - Tokenized data in CSV format for analysis
• corpus_sermo_vulgaris.xsd - XML Schema Definition for corpus validation

Project Structure

NLP_LAT_COLL/
├── SatyriconFullText.txt
├── SatyriconSelectedText.txt
├── corpus_sermo_vulgaris.xml
├── corpus_sermo_vulgaris_token.csv
├── corpus_sermo_vulgaris.xsd
├── README.md
└── LICENSE

Usage

Working with XML Data

The XML corpus follows the schema defined in corpus_sermo_vulgaris.xsd. Load the corpus using XML parsers:

import xml.etree.ElementTree as ET
tree = ET.parse('corpus_sermo_vulgaris.xml')
root = tree.getroot()

Analyzing Tokenized Data

The CSV file contains tokenized Latin text. Load it with pandas or similar tools:

import pandas as pd
df = pd.read_csv('corpus_sermo_vulgaris_token.csv')

Text Analysis

Use the provided text files for direct text analysis and processing tasks.

Data Format

XML Format

• Structured linguistic annotations
• Compliant with schema in corpus_sermo_vulgaris.xsd
• Suitable for validation and complex queries

CSV Format

• One token per row
• Columns for lemmatization, part-of-speech, and morphological features
• Efficient for statistical analysis

Requirements

• Python 3.7+
• Libraries: pandas, lxml (optional for advanced XML processing)

Installation

Clone the repository:

git clone https://github.com/Bestroi150/NLP_LAT_COLL.git
cd NLP_LAT_COLL

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Bestroi150

Citation

If you use this corpus in academic work, please cite:

@dataset{nlp_lat_coll,
  title={NLP Latin Collection: Satyricon Corpus},
  author={Kristiyan Simeonov},
  year={2023},
  url={https://github.com/Bestroi150/NLP_LAT_COLL}
}

Contributing

Contributions are welcome! Please feel free to submit pull requests or open issues for improvements and suggestions.

Disclaimer

This corpus is provided for educational and research purposes. Users are responsible for complying with any applicable licensing restrictions related to classical texts and their derivatives.