WordNet is a semantically oriented dictionary of English, similar to a traditional thesaurus but with a richer structure.
WordNet is a part of NLTK and you will use WordNet later in this module to identify the` correct` sense of a word (i.e for word sense disambiguation).
Another important resource for semantic processing is ConceptNet which deals specifically withassertions between concept.For example, there is the concept of a “dog” ,and the concept of a”kennel”. As a human, we know that a dog lives inside a kennel. ConceptNet records that assertion with /c/en/dog /r/AtLocation /c/en/kennel.
ConceptNet is arepresention that provides commonsense linkage between words.For example,it states that bread is commonly found near toasters. These everyday fact could be useful if ,for e.g,you wanted to make a smart chatbotwhich says – “Since you like toasters, do also like bread? I can order some for you.”
But, unfortunately, ConceptNet isn’t organized as well as one would want. For instance, it explicitly states that a toaster is related to an automobile. This is true since they are both mechanical machines, but you wouldn’t want for e.g. a chatbot to learn that relationship in most contexts.