Chatbots NLP and AI in Chatbots 2

Question 1

What is 'Named Entity Recognition' (NER) used for in chatbots?

Accepted Answer

Automatically identifying and classifying key information like people, places, and dates in text

Answer

Naming bot personas

Answer

Generating bot responses

Answer

Monitoring server performance

Question 2

How does a transformer-based model like BERT improve chatbot NLP?

Accepted Answer

By understanding context bidirectionally, capturing word meaning based on surrounding text

Answer

By using simple keyword matching

Answer

By reducing training data needs to zero

Answer

By eliminating the need for entities

Question 3

What is 'slot filling' in task-oriented chatbots?

Accepted Answer

Collecting all required pieces of information (slots) from the user to complete a specific task

Answer

Populating a database table

Answer

Writing code for API integrations

Answer

Designing the chat UI

Question 4

What is 'dialogue state tracking' in a conversational AI system?

Accepted Answer

Maintaining a representation of what has been established in the conversation so far

Answer

Recording chat logs to a file

Answer

Tracking user location

Answer

Monitoring API uptime

Question 5

What distinguishes a 'generative' chatbot from a 'retrieval-based' chatbot?

Accepted Answer

Generative bots produce new text responses using language models; retrieval bots select from predefined answers

Answer

Generative bots use databases; retrieval bots use APIs

Answer

Generative bots are always more accurate

Answer

Retrieval bots cannot handle multiple languages

Question 6

What is 'zero-shot learning' in the context of chatbot NLP?

Accepted Answer

The model's ability to handle new intents it was never explicitly trained on by generalizing from context

Answer

Training a model with no data

Answer

Running the bot without internet

Answer

Skipping the testing phase