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.
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