zpwiki/pages/interns/dries_huybens/README.md

title	published	taxonomy
Dries Huybens	true	category tag author erasmus nlp ie rag medical Daniel Hladek

ERASMUS Intern Summer 2026, 20 July - 30 August

Topic:

Multilingual Knowledge Graphs from medical data

Goal:

• Construct a knowledge graph from medical package inserts in multiple languages
• Utilize the graph in an intelligent agent that recommends medication.

Tasks:

• Continue project of Bogdan Paul Chis

• Study repositories:

  • https://github.com/chis-facultate/erasmus-kosice
  • https://github.com/hladek/mul-me-kg
  • https://github.com/hkuds/lightrag

• Learn intelligent agents and generative models - OpenAI API, Agent frameworks, RAG systems.

• Learn about knowledge graphs and GraphRAG. Read several research papers.

• Prepare a Python based workflow, use git code repository

• Visualize the graph

• Prepare an agent that utilizes the unstructured data and graph-data.

• Evaluate the agent using DeepEval or RAGAS.

• Write a report

• Put all code to GIT

Project tasks update:

• Prepare a multilingual parallel corpus from OPUS data
• Prepare dataset for visual language model evaluation from foto
• Prepare dataset for visual language model evaluation from wikipedia
• Prepare corpus of text and image data from pravda.sk

Outupus:

• multilingual corpus was analyzed with embedding models. Semantic overlap between languages is low, so multilngual parallel corpus will be small.
• A corpus from FotkyZadarmo.sk