A tutorial in German language for children Processing and Python It is easy to get our hands on millions of words of text. What can we do with it, assuming we can write some simple programs? What can we achieve by combining simple programming techniques with large quantities of text? How can we automatically extract key words and phrases that sum up the style and content of a text?
What tools and techniques does the Python programming language provide for such work? What are some of the interesting challenges of natural language processing? This chapter is divided into sections that skip between two quite different styles. In the “computing with language” sections we will take on some linguistically motivated programming tasks without necessarily explaining how they work. In the “closer look at Python” sections we will systematically review key programming concepts. We’ll flag the two styles in the section titles, but later chapters will mix both styles without being so up-front about it.
If the material is completely new to you, this chapter will raise more questions than it answers, questions that are addressed in the rest of this book. 1 Computing with Language: Texts and Words We’re all very familiar with text, since we read and write it every day. But before we can do this, we have to get started with the Python interpreter. Type “help”, “copyright”, “credits” or “license” for more information. If you are unable to run the Python interpreter, you probably don’t have Python installed correctly. Python interpreter is now waiting for input.
Once the interpreter has finished calculating the answer and displaying it, the prompt reappears. This means the Python interpreter is waiting for another instruction. Your Turn: Enter a few more expressions of your own. The preceding examples demonstrate how you can work interactively with the Python interpreter, experimenting with various expressions in the language to see what they do. In Python, it doesn’t make sense to end an instruction with a plus sign. Now that we can use the Python interpreter, we’re ready to start working with language data. 2 Getting Started with NLTK Before going further you should install NLTK 3.