Automated reasoning homework 2015

Automated reasoning homework as a second part of a two-phase project

The goal of this homework is

• to learn about representing knowledge and rules in logic
• experimenting with an automated reasoner

The concrete task is to add some common sense rules to the rdf or multi-arity representation output of the first phase of the project and then ask and prove some example queries using an automated reasoner.

Administrative

Homework defence deadline: 24. November. Presentation afer this deadline will give half of the points. Absolute deadline is 8. December: no submissions will be accepted after that,.

Work should be submitted to git, latest one day before deadline.

The groups are same as for the first phase

What you have to do

First of all, by default we will use the otter prover. Download it and try out some example problems in the otter zip file. Have a look at the manual as well.

Suppose you have a triplet like

  [http://en.wikipedia.org/wiki/Barack_Obama,
   http://en.wikipedia.org/wiki/china],
   id:type
   http://conceptnet5.media.mit.edu/web/c/en/person

where the list http://en.wikipedia.org/wiki/china means that we do not know which interpretation is the correct one (the original word was like he,this,she,it,...)

First, pick just one interpretation like

   http://en.wikipedia.org/wiki/Barack_Obama,
   id:type
   http://conceptnet5.media.mit.edu/web/c/en/person

and then

• represent it in otter format
• add common sense rules about the domain of news and politics (ontology: like a taxonomy, can be a bit more complex)
• pose a question in otter format
• run otter to find answer

If you manage to do that, you will pass.

Next, a bit fancier task:

Run a loop where you try out different interpretations of he,this,she,it,... and for each interpretation in the list:

• represent it in otter format
• add common sense rules about the domain of news and politics (ontology: like a taxonomy, can be a bit more complex)
• check whether otter generates a contradiction: if yes, then this is probably a wrong interpretation, since it does not match common sense rules.

Examples

The following examples are in the Otter format: the first two are in the clause syntax and are similar to what you are expected to in the third lab. The last one demonstrates formula syntax, calculation and probabilities (kind of).

• Derive simple information about Obama
• Ask a query about Obama
• Probabilities and web scraping Determine the type of objects using information from a web page and probability-like measures.