Chatbots for Beginners: A Complete Guide to Build Chatbots - Machine Learning-Based Chatbots: Remove Tags and Lemmatize

The video tutorial explains the process of removing unwanted tags from text data using a dictionary and the RE function. It then covers appending text, POS tagging, and creating a tag map for adjectives, verbs, and adverbs using Wordnet. The tutorial also details the lemmatization process, including developing a function to generate a lemma list. Finally, it concludes with a brief mention of the next steps in the video series.

What is the primary purpose of creating an empty dictionary in the process of removing tags?

• To list all possible tags

• To store the original text

• To keep track of removed tags

• To store cleaned words

Which function is used to substitute and remove specific tags from the dataset?

• RE.remove

• RE.delete

• RE.substitute

• RE.replace

What is the next step after removing unwanted tags from the text?

• Generating responses

• POS tagging and lemmatization

• Creating a new dictionary

• Analyzing the dataset

In POS tagging, which category is NOT mentioned for word classification?

• Nouns

• Pronouns

• Adverbs

• Adjectives

What is the purpose of the WordNet lemmatizer in the process?

• To generate responses

• To create a list of lemmatized words

• To remove unwanted tags

• To categorize words into different parts of speech

Where are adjectives stored in the tagging map?

• In the matrix place J

• In the matrix place V

• In the matrix place R

• In the matrix place N

What is the focus of the next video as hinted in the conclusion?

• Developing a new function

• Generating welcome inputs and responses

• Removing additional tags

• Analyzing the dataset