Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI

Knowledge Graphs meet Language Models (Sommersemester 2022)

Dozent: Prof. Dr. Felix Naumann (Information Systems) , Nitisha Jain (Information Systems) , Alejandro Sierra Múnera (Information Systems)
Website zum Kurs: https://hpi.de/teaching/current-courses/ss-22/knowledge-graphs-meet-language-models.html

Allgemeine Information

  • Semesterwochenstunden: 2
  • ECTS: 3
  • Benotet: Ja
  • Einschreibefrist: 01.04.2022 - 30.04.2022
  • Lehrform: Seminar
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch
  • Maximale Teilnehmerzahl: 12

Studiengänge, Modulgruppen & Module

IT-Systems Engineering MA
  • OSIS: Operating Systems & Information Systems Technology
    • HPI-OSIS-K Konzepte und Methoden
  • OSIS: Operating Systems & Information Systems Technology
    • HPI-OSIS-S Spezialisierung
  • OSIS: Operating Systems & Information Systems Technology
    • HPI-OSIS-T Techniken und Werkzeuge
Data Engineering MA


Knowledge Graphs represent information from real-world entities and their relationships in a graph structure. Their construction, representation, and completion have been active research topics in the last few years.

On the other hand, information have also been represented through natural language in vast amounts of documents throughout the history of humanity and recently large language models have been trained to embed this textual information in dense vector spaces.

In this seminar we are going to study the basic concepts of knowledge graphs (creation and completion) and language model training, and then we will concentrate on recent research that have tried to combine both approaches.


  • Good understanding of machine learning and neural network


  • Gerhard Weikum, Xin Luna Dong, Simon Razniewski and Fabian Suchanek (2021), "Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases", Foundations and Trends® in Databases: Vol. 10: No. 2-4, pp 108-490. http://dx.doi.org/10.1561/1900000064
  • Dan Jurafsky and James H. Martin, "Speech and Language Processing" (3rd ed. draft) https://web.stanford.edu/~jurafsky/slp3/

Lern- und Lehrformen

Students will learn to...

  • Read and understand scientific publications
  • Analyze and summarize research contributions


  • Paper presentation 30%
  • Final poster and presentation 70%


Date Topic
April 18 Holiday
April 25 Organization & Preview
May 2 Introduction session
May 9 Paper discussion
May 16 Paper discussion
May 23 Paper discussion
May 30 Paper discussion
June 6 Holiday
June 13 Paper discussion
June 20 Paper discussion + Introduction to Part 2
July 11 Paper consultation
July 25 Final Poster Session