For the course in the winter semester 2021, please see here!
Content
In this class, we will take an overview of Information Extraction for Knowledge Base Construction. This is the process of deriving structured information (such as alive(Elvis)) from digital text (such as the sentence "Elvis is alive"). We will first see applications of information extraction, notably in question answering systems, chatbots, and personal assistants. Then, we will cover the technical steps of knowledge base construction: natural language processing, named entity recognition, entity disambiguation, instance extraction, fact extraction, and knowledge cleaning.
Grading
The course is graded by 6 labs and a final exam.
Final grade: 50% labs + 50% exam
Final grade at re-take: 50% original labs + 50% reexam
Modalities:
It is not allowed to use code from other sources (students, Web, libraries, etc.) that was designed to solve the problem of the lab. Example: If the task is POS-tagging, it is not allowed to use a library or a piece of code from the Web for POS-tagging for this lab.
Discussing assignments together is allowed, but each student must write their own solution.
No sharing of code!
Plagiarism entails a grade of 0 for the lab/exam.
Schedule
The course takes place on Thursday afternoon, 13:30-16:30. Due to the Corona pandemic, the course will take place online in Zoom here.