Overview:

The objective of this ambitious project is to establish a comprehensive, adaptable Natural Language Understanding (NLU) system, utilizing state-of-the-art Machine Learning (ML) methodologies and programming languages like Python and Prolog. The system would integrate capabilities for lexical analysis, syntactic analysis, and semantic analysis, establishing a robust language understanding framework. A significant feature of this system would be its ability to interact dynamically with a knowledge database, adjusting its responses based on real-time information updates.

Key Features:

1. Lexical Analyzer: Using ML techniques, this component will tokenize the input and generate a list of tokens, facilitating the breakdown of a given text into meaningful segments.

2. Syntactic Analyzer: This module will analyze the structure of the input, ensuring the correct grammatical structure and identifying the relations between different components within the sentences.

3. Semantic Analyzer: Going beyond syntax, the semantic analyzer will comprehend the meaning of the text. It will correlate words and sentences to their true intent, effectively grasping the context behind the given inputs.

4. Adaptable NLU Module: Built on the foundational layers of lexical, syntactic, and semantic analyzers, this sophisticated NLU system will interact naturally and adapt its responses based on the given context.

5. Dynamic Knowledgebase Integration: A distinctive characteristic of this system is its seamless interaction with a knowledge database. The system can fetch, understand, and incorporate real-time information from the database, providing relevant and updated responses to user inputs.

Technologies and Languages Used: Python, Prolog, Machine Learning, Natural Language Processing (NLP), NLU Techniques, Database Management

The expected outcome of this project is a comprehensive NLU system that can effectively understand, interpret, and respond to natural language inputs, boasting an enhanced capability to adapt to the constantly evolving information in a knowledge database. This project will pioneer a new frontier in NLU systems, making them more responsive, adaptable, and intelligent. The goal of this project is to create the following, via Machine Learning Language and more specifically, Python and Prolog:

• A Lexical Analyzer.
• A Syntactic Analyzer.
• A Semantic Analyzer.
• An Adaptable Natural Language Understanding Project, which can interact with an Knowledge Database at any time.

You can find further information regarding the development of this project under the project's documentation file - see the Documentation for details.

This project is licensed under the MIT License - see the LICENSE file for details

• Panagiotis Apostolopoulos
• Dimitris Matsanganis
• Alexandros Scarpelos