This repository contains the code for a web-based application form created for the Multilingual Corpus of the AQUILIGN — Multilingual Aligner and Collator project.
The application was built using Streamlit to facilitate the structured collection, organization, and storage of textual data for historical and linguistic research.
The primary goal of this application is to streamline the collection process of historical multilingual texts by allowing users to insert, organize, and store textual data in a structured format.
This tool ensures that all textual sources are well-documented, traceable, and accessible for further analysis. It provides an interface for submitting texts, viewing statistical insights, and managing stored records.
📌 Links:
- Application Form (Currently private)
- Compiled Data CSV
This dataset is intended for training machine learning models for text segmentation—a key task in breaking down texts into meaningful linguistic units. This work is crucial for improving text accessibility and analysis, particularly for historical documents.
The corpus primarily consists of prose texts from the 13th to 15th centuries, with the possibility of extending into the mid-16th century. Texts have been selected based on thematic diversity to create a rich dataset for model training and research purposes.
The application consists of four main pages:
- App – The main form for text submission.
- Display TXT – View and convert XML files to plain text.
- Stats – Visualize statistical insights about the uploaded texts.
- Texts – Manage and search all submitted texts.
This page allows users to input detailed metadata about each text, including:
- Source information
- File uploads (TXT and/or XML)
- Mandatory fields (marked with
*)
🚨 Note: Certain fields are required before submission to ensure completeness.
- View and convert XML files into plain text format for easier readability and processing.
- Provides automatically generated statistics based on the submitted corpus.
- Helps analyze trends, distribution, and text characteristics.
- View all submitted texts in a searchable format.
- Download texts as CSV for external use.
- Modify or delete entries as needed.
The texts within this corpus are released under the CC BY-NC-SA license. This allows:
✅ Adaptation, remixing, and further development
✅ Non-commercial use
✅ Proper attribution to original authors
✅ Sharing under the same licensing terms
For full details and source citations, refer to the "sources" and "corpus" columns in the compiled data CSV.
Contributions are welcome! Please fork this repository and submit a pull request for any enhancements or bug fixes.
For questions or suggestions, please open an issue in this repository.
- Clone the Repository
git clone https://github.com/carolisteia/mulada.git cd mulada - Install dependencies
pip install -r requirements.txt
- Run the Streamlit App
streamlit run app.py
- Access the Application Open your browser and navigate to http://localhost:8501
mulada/
├── backup/ # Backup files
├── data/ # Data files
├── pages/ # Streamlit pages
├── txts/ # Text files
├── utils/ # Utility scripts
├── xmls/ # XML files
├── .gitignore # Git ignore file
├── app.py # Main application script
├── data.csv # Compiled data CSV
├── options.py # Options configuration
├── requirements.txt # Python dependencies
└── xmls.py # XML processing script