Bio Semantic Parsing

This project focuses on building a pipeline that automates the extraction and transformation of biological research data into a structured logical format using advanced Large Language Model (LLM) prompting techniques.

By converting unstructured biomedical data into formal representations (MeTTa / First-Order Logic), the pipeline enables seamless integration into Atomspace — supporting efficient, data-driven reasoning and knowledge representation.

✨ Current Implementation

• Data Source: GEO (Gene Expression Omnibus)
• Functionality:
  • Accepts a GSE ID
  • Loads the associated paper abstract from PubMed
  • Converts both the abstract and GSE metadata into MeTTa format
  • Prepares the data for Atomspace representation

🛠️ Installation & Usage

1. Clone the Repository

git clone https://github.com/iCog-Labs-Dev/bio-semantic-parser.git
cd bio-semantic-parser

2. Set Environment Variables

Create a .env file in the root directory of the frontend and backend folders and add the necessary keys.

3. Navigate to Backend Directory

cd Backend

4. Build Docker Containers

docker compose build

5. Start the Application

docker compose up

6. Access the Web Interface

After the build is complete and the server is running, open your browser and visit:

http://localhost:3030/

You should see the Bio Semantic Parsing interface ready to accept GSE IDs.