This document discusses semantic analysis and ambiguity in language. Semantic analysis is the process of drawing meaning from text by analyzing grammatical structure and word relationships. There are several types of ambiguity that can arise in both written and spoken language due to multiple meanings of words or different pronunciations of words. The document then outlines several important elements of semantic analysis, such as hyponyms and synonyms. It describes how semantic analysis can be applied to tasks like information extraction, text summarization, and machine translation. Finally, it provides references for further reading on semantic analysis and related topics.

1. Powerpoint (Slidesgo)
Do you really want to
understand Meaning in
text?

2. CONTENTS
What is Ambiguity?
2
01
Understand Meaning in text
02
Application in SA
03

3. What is Ambiguity?
01

4. 4
Language
Speaking
Written

5. Written texts, results from multiple meanings of a word,
and in spoken language, results from different word forms
of the same sounds.
What is Ambiguity?

6. Textual Ambiguity

7. Spoken Ambiguity

8. Do you want to
understand meaning
in text?
02

9. (Understand Meaning)
Semantic analysis is the process
of drawing meaning from text. It
allows computers to understand
and interpret sentences,
paragraphs, or whole documents,
by analyzing their grammatical
structure, and identifying
relationships between individual
words in a particular context.
Semantic Analysis
I got it..

10. Elements of Semantic Analysis
Some important elements of semantic analysis
1. Hyponyms
2. Meronomy
3. Polysemy
4. Synonyms
5. Antonyms
6. Homonyms

11. Hyponymy
Specific lexical items of a generic
lexical item (hypernym)
e.g. orange is a hyponym of fruit
(hypernym).

12. Meronomy
A logical arrangement of text and
words that denotes a constituent
part of or member of something
e.g., a segment of an orange

13. Polysemy
Head
Hit with
the head
Boss of a
business
Top of
anything
Go
towards
Brain
Chief
teacher
title

14. Synonyms

15. Antonyms

16. Homonyms
Both polysemy and homonymy words
have the same syntax or spelling. The
main difference between them is that
in polysemy, the meanings of the
words are related but in homonymy,
the meanings of the words are not
related.

17. Application in SA
03

18. Semantic Classification Models
1. Topic Classification
2. Sentiment Analysis
3. Intent Classification
Semantic Extraction Models
1. Keyword Extraction
2. Entity Extraction
Application in Semantic Analysis
1. Information Extraction
2. Text summarization
3. Information Retrieval
4. Machine Translation
Semantic Analysis Techniques

19. Related Link
★ https://www.tutorialspoint.com/natural_language_proce
ssing/natural_language_processing_semantic_analysis.h
tm
★ https://www.atlantis-
press.com/journals/ijndc/125905844/view
★ https://dl.acm.org/doi/fullHtml/10.1145/3325885
★ https://monkeylearn.com/blog/semantic-analysis/
★ https://en.wikipedia.org/wiki/Semantic_analysis_(lingui
stics)
★ https://www.cs.tut.fi/sgn/arg/klap/introduction-
semantics.pd
★ https://www.expert.ai/blog/natural-language-process-
semantic-analysis-definition/
★ https://zetaglobal.com/blog/what-is-semantic-analysis/
References
Paper Title
★ A Context-Sensitive Homograph Disambiguation
★ Difference-Between-Lexical-and-Structural-Ambiguity
★ Thai Word Sense Disambiguation Using Cross Language
Knowledge Sources Approach
★ Subjectivity Word Sense Disambiguation
★ Myanmar Homonym Disambiguation System
★ Effective Approach of Semantic Analysis to NLP (English-
Myanmar Language)

20. Does anyone have
any questions?
THANKS!