Simulated Example for NLP IA1 (2)
Internal Assessment 1 - Solutions for Natural Language Processing
Date: 17/02/26
| Q. No. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | Total Marks |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mark Awarded | 10 | 09 | 19 |
| Q1 | Solve any Two |
|---|---|
| i. | Define NLP. What are the different ambiguities in NLP. |
| ii. | Explain N-gram Language model. |
| iii. | Compare inflectional morphology and derivational morphology. |
→ NLP is the spoken language such as hindi, english, french, spanish opposed to the programming language such as Java, python, C, C++ which are the programming language.
→ The input and the output of this can be in two forms which are:
• written text
• speech
→ The natural language processing is which converts the human language into the computer language. There are different ambiguities in the natural language processing which are as follow as-
The different ambiguities in NLP are as follow as:
• Lexical/Morphological
• phonetic
• semantic
• synaptic
Lexical/Morphological
In the morphological the complete word break down into small words for example the words such as:
truth + ful + ness = Truthfulness
decele + negt + success + ful = Successful
phonetic
The multiple word has single pronunciation
The meaning of the word is also different in it but the pronunciation of the word is similar.
For example:
(write, right)
This both words are pronounced as "rite"
The pronunciation of both words is the same but the spelling and meaning of the word is different.
Semantic
In semantic, the sentence can also have multiple or different meaning in this ambiguity.
for example:
The chicken is ready to eat
It can have two meanings:
- The chicken will eat
- The chicken which is cooked is ready to eat
Syntactic
In this ambiguity, the single sentence can have different interpretation of the single sentence.
for example:
From a car, I saw the poll is moving.
→ car is moving
→ poll is moving
In the above sentence, this ambiguity in NLP is explained.
Inflectional Morphology
• In this type of morphology the meaning of the word remains same.
• The tense of the word is only changed in Inflectional morphology.
• Example:- dog → dogs, Cat → cats, Tall → Tall, kill → killed
Derivational Morphology
• In this type of the morphology the meaning of the word also change.
• The whole meaning of the word is changed in the derivational Morphology.
• Example:- faithful → unfaithful, kind → unkind, Teach → Teacher, Truth → Lie
In the above example the meaning of the word remains same. In the above example the meaning of the word change. In dictionary, the meaning of the word is different. In the dictionary, the meaning of the word is same.
Inflectional and derivational morphology are the types of different morphology. Compounding and Clitization morphology are also the different type of morphology.
| Q2 | Solve any Two |
|---|---|
| i. | Explain the various challenges in NLP. |
| ii. | Differentiate between Stemming and Lemmatization. |
| iii. | What are Regular Expression (RE)? Explain the meaning of the given RE: • a. [e^] • b. [^A-Z] |
| Stemming | Lemmatization |
|---|---|
| Stemming does not use dictionary | Lemmatization uses the dictionary |
| Stemming gives less accurate answers | Lemmatization has more accuracy than stemming |
| Stemming is simple than lemmatization | Lemmatization is slower than stemming |
| In Stemming, word | Stemma | In lemmatization, word | Lemmatization, lemmatization |
|---|---|---|---|
| Studies | Studi | Studies | Study |
| Studying | Study | Studying | Study |
| Ninaz | Nin | Ninaz | Nino |
| Ninez | Nin. | Ninez. | Ninez. |
In the studies, the (studi) is not the real word and we cannot find the meaning also of studi in the dictionary.
From the above example the word is studies and after that it is "study" which is the correct word and we can also find it meaning in dictionary.
| word | stemming | lemmatization |
|---|---|---|
| Informative | Inform | Informative |
| Information | Inform | Information |
| Studier | Studi | Study |
The various challenges in NLP (Natural language processing) are as follow as given below i-
-
The challenges which are faced in the NLP can be the information of the word can also be wrong sometimes.
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If the word is given as studier, if we use the stemma the word will be studi, but problem is the meaning of the word will not be found in dictionary and the word 'studi' is also wrong.
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Sometime it may be difficult to convert the human language into the computer language. This also may cause a problem and we may face challenges in the natural language processing.
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When the data is given to the pre-procesor the data needs cleaning as it removes space between the words and converts the word, if the given word is wrong. It also may be difficult to find correct word
When the text/input goes to the pre-procesor after the cleaning process it goes to the natural language processor which helps to find the meaning of given sentences one word. If the meaning of the information provided to us is wrong, it can also lead to problem.
The human language can also be difficult to understand by computers.
The input/output of the head processing, which one in written text and speech. The speech can also find the issue as it is difficult than the written text. This is also the type one of the challenge in the natural language processing.