An AI-driven Knowledge Graph of the Antiquities market: toward automatised methods to identify illicit trafficking networks The notebook allows artworks and their provenance data collection, the building of a Knowledge Graph derived from these data, through NLP enhanced event extraction, on Neo4j and the performing of different Network Analysis on the Graph.

Part of code are partially adapted from: Hebatallah Mohamed (hebatallah.mohamed@iit.it)

Author: Riccardo Giovanelli (riccardo.giovanelli@unive.it)

1. Clone this repository from your command line

git clone https://github.com/riccardogvn/AIKoGAM.git

2. Install requirements from your command line (we suggest to do so after creating a new virtual environment)

pip install -r requirements.txt

1. Launch Jupyter Lab from your command line

jupyter lab

2. From Jupyter Lab open the file AIKoGAM_notebook.ipynb and follow the notebook