The document discusses challenges in natural language processing (NLP), particularly various types of ambiguities such as lexical, syntactic, and referential ambiguity. It also outlines the advantages of NLP, including efficient communication and precise responses, while noting drawbacks like context limitations and unpredictability. The course aims to equip students with knowledge of NLP's role in tasks such as translation and information retrieval.

1. Natural Language Processing and
Information Retrieval
COURSE CODE: BTAIML703-20
Lecture No:2
Prepared By :
Anju Bala
CSE Department

2. Outline
• challenges
• The role of machine learning

3. Challenges in NLP
• Ambiguity
Lexical Ambiguity
Syntactic Ambiguity
Referential Ambiguity

4. Challenges in NLP
• Ambiguity
Lexical AmbiguityShe is looking for a match.
The fisherman went to the bank.
Syntactic Ambiguity
Referential Ambiguity

5. Challenges in NLP
• Ambiguity
Lexical AmbiguityShe is looking for a match.
The fisherman went to the bank.
Syntactic Ambiguity The chicken is ready to eat.
Visiting relatives can be boring.
Referential Ambiguity

6. Challenges in NLP
• Ambiguity
Lexical AmbiguityShe is looking for a match.
The fisherman went to the bank.
Syntactic Ambiguity The chicken is ready to eat.
Visiting relatives can be boring.
Referential Ambiguity The boy told his father the theft. He was very upset

7. Introduction
• What is NLP?
• It helps developers to organize knowledge for performing tasks
such as translation, automatic summarization, Named Entity
Recognition (NER), speech recognition, relationship
extraction, and topic segmentation.

8. Advantages of NLP
• NLP helps users to ask questions about any subject and get a direct
response within seconds.
• NLP offers exact answers to the question means it does not offer
unnecessary and unwanted information.
• NLP helps computers to communicate with humans in their
languages.
• It is very time efficient.
• Most of the companies use NLP to improve the efficiency of
documentation processes, accuracy of documentation, and identify
the information from large databases.

9. Disadvantages of NLP
• NLP may not show context.
• NLP is unpredictable
• NLP may require more keystrokes.
• NLP is unable to adapt to the new domain, and it has a limited
function that's why NLP is built for a single and specific task only.