Lab Station 4: Knowledge Representation and Knowledge Processing

The goal of LS4 is to familiarize the student with the MultiNet paradigm and the workbench for the knowledge engineer MWR. MWR is a very powerful graphical tool based on MultiNet. Thus, this lab station gives our students the opportunity to gain "hands-on" experience with knowledge representation within the MultiNet framework.

The exercises are divided into a general and an advanced part. The general part deals with the basics of MultiNet and MWR. The advanced exercises cover topics such as assimilation of networks and natural language access to databases.

Background

The core of lab station LS4 is the MultiNet-paradigm. The tasks of this station deal with problems of automatic natural language processing (NLP) and in particular with the meaning representation of natural language expressions.

The use and benefit of NLP is demonstrated using two special subjects:

Transformation of natural language queries to databases. This task shows the role NLP methods play in realizing a user friendly access to complex IT-systems.
Assimilation (accumulation) of meaning structures of single sentences into large knowledge bases representing the meaning of whole texts. This task shows the connection between NLP and knowledge acquisition.

In the first case, the tasks are evaluated by embedded programs. In the second case, the electronic tutor corrects the solution immediately by means of the MWR tool.