the parser parses the sentence as followsparser_chunking parse(sentencenextwe need to get the output the output is generated in the simple variable called output_chunk output_chunk=parser_chunking parse(sentenceupon execution of the following codewe can draw our output in the form of tree output draw(bag of word (bowmodel bag of word (bow) model in natural language processingis basically used to extract the features from text so that the text can be used in modeling such that in machine learning algorithms now the question arises that why we need to extract the features from text it is because the machine learning algorithms cannot work with raw data and they need numeric data so that they can extract meaningful information out of it the conversion of text data into numeric data is called feature extraction or feature encoding how it works this is very simple approach for extracting the features from text suppose we have text document and we want to convert it into numeric data or say want to extract the features out of it then first of all this model extracts vocabulary from all the words in the document then by using document term matrixit will build model in this waybow represents the document as bag of words only any information about the order or structure of words in the document is discarded concept of document term matrix the bow algorithm builds model by using the document term matrix as the name suggeststhe document term matrix is the matrix of various word counts that occur in the document with the help of this matrixthe text document can be represented as