Learn how chatbots break down user inputs to identify intents and entities using natural language processing (NLP). Get the key concepts for the IBM AI Fundamentals certification exam.
Table of Contents
Question
Which of the following statements describes how a chatbot processes a question?
A. The chatbot breaks inputs apart to identify intents and entities.
B. The chatbot combines entities to find how relationships divide at nodes.
C. The chatbot logs each question into a frontend database.
D. The chatbot creates frontend triggers.
Answer
A. The chatbot breaks inputs apart to identify intents and entities.
Explanation
A chatbot listens to a human’s question (an input), then analyzes it to find out what the human is talking about (entities) and what it wants to know or do about them (an intent).
When a user asks a chatbot a question, the chatbot uses natural language processing (NLP) techniques to analyze and understand the user’s input. A key part of this process involves breaking the input down into its constituent parts to identify the user’s intent (what they want to accomplish) and any relevant entities (key pieces of information).
More specifically, the NLP pipeline typically includes the following steps:
- Tokenization: The input is split into individual words or tokens.
- Named Entity Recognition (NER): The chatbot identifies and extracts entities – i.e. key information like names, dates, locations, etc.
- Part-of-Speech (POS) Tagging: Each word is tagged with its part of speech (noun, verb, adjective, etc).
- Parsing: The grammatical structure of the sentence is analyzed.
- Intent Classification: Based on patterns in the processed input, the chatbot determines the overall intent behind the user’s message.
So in summary, by breaking the input down and analyzing its components, the chatbot is able to understand the key elements of the user’s question – the intent and relevant entities – which allows it to formulate an appropriate response. The other options describe aspects not directly related to processing the user’s question.
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