Aiforkids - Recent activity in Natural Language Processing

Answer selected: Sagar is collecting data from social media platforms. He collected a large amount of data. but he wants specific information from it. Which NLP application would help him?

Wed, 13 Sep 2023 09:27:11 +0000

Automatic Summarization

Automatic summarization is the process of shortening a set of data computationally, to create a subset that represents the most important or relevant information within the original content.

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Answer selected: Samiksha, a student of class X was exploring the Natural Language Processing domain.

Mon, 13 Mar 2023 08:45:15 +0000

1. Tokenisation

Akash, and, Ajay, are, best, friends Akash, likes, to, play, football, but, Ajay, prefers, to, play, online, games

2. Removal of stopwords

Akash, Ajay, best, friends Akash, likes, play, football, Ajay, prefers, play, online, games

3. Converting text to a common case

akash, ajay, best, friends akash, likes, play, football, ajay, prefers, play, online, games

4. Stemming/Lemmatisation

akash, ajay, best, friend akash, like, play, football, ajay, prefer, play, online, game

(1 mark for each step; 1*4=4)

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Answered: Saurabh is working on NLP based project. He wanted to know about the concept where the entire corpus is being divided into sentences. Help hip and explain the concept.

Sun, 12 Mar 2023 01:34:47 +0000

This is done under Sentence segmentation, where the whole corpus is reduced into sentences

Answered: Ayushi was learning about NLP. She wanted to know the term used for the whole textual data from all the documents altogether. Help her in identifying the term used for it.

Sun, 12 Mar 2023 01:33:03 +0000

ANSWER = CORPUS

Answered: Search engines not only predict what popular searches may apply to your query as

Fri, 10 Mar 2023 09:52:18 +0000

(C)NATURAL LANGUAGE PROCESSING

Answer selected: Identify the type of chatbot with the information given below:

Wed, 08 Mar 2023 10:19:35 +0000

Script Bot

These bots work on pre-programmed instructions inside the application/machine and are generally easy to develop.
They are deployed in the customer care section of various companies.
Their job is to answer some basic queries that they are coded for and connect them to human executives once they are unable to handle the conversation.

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Answered: Which of the following is the type of data used by NLP applications?

Mon, 06 Mar 2023 01:56:19 +0000

option d ) text and speech

Answered: _____ helps in assigning a predefined category to a document, organize it in such a way that helps customers to find information they want.

Mon, 06 Mar 2023 01:53:58 +0000

Text Classification is the answer

Answered: A corpus contains 12 documents. How many document vectors will be there for that corpus?

Mon, 06 Mar 2023 01:50:59 +0000

a)12 is the correct option.

Answered: Classify the following into Smart bot or Script bot accordingly?

Sun, 05 Mar 2023 12:13:02 +0000

There are two types of chatbots: Smart bots and Script bots.

Smart Bots:

Use AI and NLP to generate responses and improve over time.
Examples: Mitsuku Bot, Clever Bot, Jabberwacky, Haptik, and Rose.

Script Bots:

Use pre-programmed scripts for responses.
An example of a script bot is OChatbot, which relies on predetermined responses based on the script it is programmed with.

Learn more about NLP and smart bots here:

NLP NOTES: https://aiforkids.in/class-10/nlp/
NLP ChatBot notes: https://aiforkids.in/class-10/nlp/#chatbots
NLP Video : https://www.youtube.com/watch?v=9jvuleVQWyE

Answered: What will be the results of conversion of the term, ‘happily’ in the process of stemming and lemmatization? Which process takes longer time for execution?

Sun, 05 Mar 2023 10:03:00 +0000

Word	Stemming	Lemmatization
Happily	happi	happy

Process that takes longer time for execution is lemmatization, because the word generated (lemma) is a meaning full word, and doing that needs high level processing.

(½ marks each for identifying the correct stem and lemma; 1 mark for identifying the correct process)

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Answer edited: What do we get from the “bag of words'' algorithm?

Sun, 05 Mar 2023 09:57:34 +0000

Bag of words gives us two things:

A vocabulary of words for the corpus
The frequency of these words (number of times it has occurred in the whole corpus)

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Answer edited: Most Important FAQs Regarding AI Chat GPT

Sat, 14 Jan 2023 12:08:22 +0000

What is ChatGPT?

ChatGPT is a large language model developed by OpenAI that can generate human-like text. It is based on the GPT (Generative Pre-trained Transformer) architecture and has been trained on a massive amount of text data.

How does ChatGPT work?

ChatGPT uses a deep neural network with a transformer architecture to generate text. It takes in a prompt, or a starting text, and generates a response based on the patterns it learned during training. The model is pre-trained on a large dataset and fine-tuned on specific task-related data.

What are the main features of ChatGPT?

Generates human-like text
Can be fine-tuned for specific tasks
Can be used for applications such as language translation, question answering, and text summarization.
Can generate text in many languages.

What are the advantages of using ChatGPT?

Can reduce the amount of manual work required for text generation tasks
Can be used to generate large amounts of text quickly
Can improve the accuracy of text generation tasks
Can be used to generate more natural-sounding text than rule-based systems

What are the limitations of using ChatGPT?

Can generate biased or incorrect text if it has learned biases from the training data
Can generate text that is not coherent or meaningful if the prompt is not well-formed
Can be computationally expensive to run, requiring a powerful GPU or TPU
Can be difficult to interpret the reasoning behind its generated text.

Edited: What is the role of modelling in an NLP based AI model?

Sat, 14 Jan 2023 04:59:40 +0000

What is the role of modelling in an NLP-based AI model?

a) Modelling in NLP helps in processing of AI model

b) Modelling is required to make an AI model

c) In NLP, modelling requires data pre-processing only after which the data is fed to the machine.

d) Modelling is used in simplification of data acquisition

Topic	Modelling (project cycle)
Type	Short Answer Type
Class	10

Answered: What is tokenization? Count how many tokens are present in the following statement: I find that the harder I work, the more luck I seems to have.

Sat, 31 Dec 2022 08:54:05 +0000

Tokenization is the process of breaking a piece of text into smaller units called tokens. These tokens can be words, punctuation marks, or other types of characters. Tokenization is an important step in many natural language processing tasks, such as text classification and machine translation, because it allows the computer to more easily process and analyze the text.

In the statement "I find that the harder I work, the more luck I seems to have," there are 11 tokens. There are eight words ("I", "find", "that", "the", "harder", "I", "work", "the") and three punctuation marks (" ", ",", " ").

Answered: What is tokenization? Count how many tokens are present in the following statement: I find that the harder I work, the more luck I seems to have.

Sat, 31 Dec 2022 07:22:29 +0000

Tokenization is the process of breaking down a larger piece of text into smaller units, called tokens. These tokens can be individual words, phrases, symbols, or even subwords.

In the given statement, "I find that the harder I work, the more luck I seems to have," there are 15 tokens. The individual tokens are: "I," "find," "that," "the," "harder," "I," "work," "," "the," "more," "luck," "I," "seems," and "to," "have."

It's worth noting that the tokenization process can vary depending on the specific language and the intended use of the tokens. For example, in natural language processing tasks, it is common to treat punctuation marks as separate tokens, while in other contexts they may be grouped with the adjacent words.

Answered: What is the meaning of (a) Syntax and (b) Semantics in NLP?

Tue, 14 Jun 2022 01:26:07 +0000

(a) Syntax- The grammatical structure of a sentence is called Syntax.

(b) Semantics- The meaning of the sentence is called Semantics.

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Answered: What will be the output of the word ‘cities’ after the lemmatization and stemming process?

Sun, 12 Jun 2022 06:20:57 +0000

Lemmatization: City

Stemming: Citi

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Answered: Explain the role of NLP in the sentiment analysis of human beings

Sun, 12 Jun 2022 06:18:31 +0000

We can use sentiment analysis to predict the general emotion of a text. The goal of sentiment analysis is to identify sentiment among several posts or even in the same post where emotion is not always explicitly expressed. Companies use Natural Language Processing applications, such as sentiment analysis, to identify opinions and sentiments online to help them understand what customers think about their products and services.

For example, I love this car, or I don’t like this product and will never purchase it in the future.

Sentiment analysis understands sentiment in context to help better understand what’s behind an expressed opinion, which can be extremely relevant in understanding and driving purchasing decisions.

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Answered: For the situation given above: 1. Write the problem statement template. 2. Why do we need to collect data? 3. What does an NLP-based AI model require?

Sun, 12 Jun 2022 04:10:48 +0000

1. The problem statement template for the given scenario would be:

Our	companies who are selling products and services.	Who?
have a problem that	they are not being able to expand their business to a broader audience	What?
while	they need a platform to accelerate their business and provide instant and real-time assistance.	Where?
An ideal solution would be	to implement a chatbot to cater to customer complaints and generic requests.	Why?

2. Data collection is essential in order to understand the customer’s queries and requirements, after which the computer can interpret the words and their meanings.

3. An NLP-based AI model requires normalized text with a minimum vocabulary, which was obtained as a result of data cleaning and pre-processing during the data exploration phase.

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Answered: How does text normalization reduce the vocabulary of a corpus?

Sun, 12 Jun 2022 03:54:17 +0000

In text normalization, the text is reduced to a minimum vocabulary by—

(i) eliminating stop words, special characters, and numbers from the vocabulary of a corpus.

(ii) Deleting the affixes and converting the words to their base form using stemming and lemmatization.

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Answered: Through a step-by-step process, calculate TFIDF for the given corpus:

Sun, 12 Jun 2022 03:53:34 +0000

Step 1: Create document vectors for the given documents (Term Frequency Table):-

To	The	Swinging	and	ringing	of	bells	rhyming	chiming
1	1	1	1	1	0	0	0	0
0	1	0	0	0	1	3	0	0
0	1	0	0	0	1	4	0	0
0	0	0	0	0	0	3	0	0
1	1	0	1	0	1	1	1	1

Step 2: Record the occurrence of the word in the document using the term frequency table (Document Frequency Table):-

To	The	swinging	and	ringing	of	bells	rhyming	chiming
2	4	1	2	1	3	11	1	1

Step 3: Draw the inverse document frequency table wherein, we need to put the document frequency in the denominator while the total number of documents is the numerator. Here, the total number of documents is 5, hence inverse document frequency becomes:-

To	The	swinging	and	ringing	of	bells	rhyming	chiming
5/2	5/4	5/1	5/2	5/1	5/3	5/11	5/1	5/1

Step 4: The formula of TFIDF for any word W becomes: TFIDF(W) = TF(W) * log (IDF(W)):-

To	the	swinging	and	ringing	of	bells	rhyming	chiming
1*log(5/2)	1*log(5/4)	1*log(5/1)	1*log(5/2)	1*log(5/1)	0*log(5/3)	0*log(5/11)	0*log(5/1)	0*log(5/1)
0*log(5/2)	1*log(5/4)	0*log(5/1)	0*log(5/2)	0*log(5/1)	1*log(5/3)	3*log(5/11)	0*log(5/1)	0*log(5/1)
0*log(5/2)	1*log(5/4)	0*log(5/1)	0*log(5/2)	0*log(5/1)	1*log(5/3)	4*log(5/11)	0*log(5/1)	0*log(5/1)
0*log(5/2)	0*log(5/4)	0*log(5/1)	0*log(5/2)	0*log(5/1)	0*log(5/3)	3*log(5/11)	0*log(5/1)	0*log(5/1)
1*log(5/2)	1*log(5/4)	0*log(5/1)	1*log(5/2)	0*log(5/1)	1*log(5/3)	1*log(5/11)	0*log(5/1)	0*log(5/1)

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Answered: For the situation given above.1. Create a 4W Project Canvas for this situation. 2. Can you create a model for managing such a situation? 3. Write two types of chatbots.

Sun, 12 Jun 2022 03:44:10 +0000

1. Who Canvas—Who has the problem?

Who are the stakeholders?	Students and their institutions are the stakeholders.
What do we know about them?	Students for not receiving timely notifications about important information and institutions for having a negative impact on enrolments.

2. Where Canvas—What is the nature of the problem?

What is the problem?	Due to lack of timely information, students frequently miss campus interviews, training and placement programs and other information regarding holidays and special announcements.
How do you know it is a problem?	Students should receive timely information.

3. Where Canvas—Where does the problem arise?

What is the context/situation in which the stakeholders experience this problem?

• When students miss important information regarding their careers.
• Institutions lose credibility and reputation due to the lack of communication process.

4. Why Canvas—Why do you think it is a problem worth solving?

What would be of key value to the stakeholders?	• Students get timely information and even they can share their concerns related to any facility. • Institutions get a medium to help students with admissions, student support and providing immediate access to information.
How would it improve their situation?	• Students would be able to get every information they need and connect with the institute round the clock. • Institutions can attract potential students in an effective and engaging manner.

2. The model to manage the above situation would be deploying a chatbot. Chatbots provide automated responses to prospective student queries and help them carry out basic tasks.

3. (i) Rule-based chatbot

(ii) Smart bot using ML

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Answer selected: List two possible reasons for an AI model not being efficient.

Sun, 12 Jun 2022 03:40:21 +0000

1. Lack of training data

2. Insufficient or wrong data

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Answer selected: Observe the graphs carefully and classify them according to how well the model’s output (dashed lines) matches the data samples (crosses):

Sun, 12 Jun 2022 03:40:09 +0000

(i) In the first graph, the model’s performance tries to cover all data samples, even if they aren’t aligned with the true function. This model is thought to be overfitting, with decreased accuracy.

(ii) In the second graph, the model’s performance equals the true function, indicating that the model has optimal accuracy and is referred to as a perfect fit.

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Answered: Identify any two stopwords in the given sentence:

Sun, 12 Jun 2022 03:25:07 +0000

Two stopwords in the sentence are: is, that

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Answered: How many tokens are there in the sentence given below?

Sun, 12 Jun 2022 03:19:17 +0000

There are 43 tokens in the above sentence.

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Answered: Differentiate between stop words and frequent words.

Sat, 11 Jun 2022 10:09:09 +0000

Stopwords	Frequent Words
Stopwords are those words which are used mostly repeated in the corpus but do not provide any information regarding corpus. They are filtered out before or after processing of text.	After filtering the stop words, the occurrence level drops drastically and the words which have adequate occurrence in the corpus are said to have some amount of value and are termed as frequent words.

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Answered: What is sentence segmentation in text normalization?

Sat, 11 Jun 2022 02:55:28 +0000

In text normalization, the whole text is divided into different sentences. This process is known as sentence segmentation. Each sentence is taken as a different data.

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Answered: What is an example of automatic summarization?

Fri, 10 Jun 2022 10:15:02 +0000

Media Monitoring, Newsletters, Video Scripting, and Automated Content Creation are examples of automatic summarization.

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Answered: How Virtual Assistants works?

Fri, 10 Jun 2022 08:15:53 +0000

Virtual Assistant runs on the algorithm which can interpret the voice commands and detect our speech in the database. On the basis of the interpretation and algorithm, VAs initiate the work. They can upgrade themselves with new skills, to provide better services.

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Answered: What are Virtual Assistants? Write its two characteristics.

Fri, 10 Jun 2022 08:11:53 +0000

Virtual Assistant is one of the most common applications of NLP. Virtual Assistants is available in the form of Application only or a combination of device loaded with application.

Characteristics of Virtual Assistants (VA):

(i) VA helps in performing our tasks easily and quickly.

(ii) VA helps in multi-tasking. It means VAs works their assigned task, during that you can do your own other work.

(iii) VAs access our data to accomplish the assigned task.

(iv) Generally Virtual Assistants works on voice command.

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Answered: What is the intention of NLP?

Fri, 10 Jun 2022 08:08:10 +0000

The main intention of NLP to bridge the gap between human language and the way computer understand it.

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What is linguistics?

Fri, 10 Jun 2022 08:02:15 +0000

What is linguistics?

Topic	NLP
Type	Very short answer type
Class	10

Answered: The customer care section of various companies includes which type of chatbot? and write features of that bot.

Fri, 10 Jun 2022 02:58:02 +0000

The customer care section of various companies includes scriptbots.

Its features are-

Script bots are easy to make
Script bots work around a script which is programmed in them
Mostly they are free and are easy to integrate to a messaging platform
No or little language processing skills
Limited functionality
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Answered: What are the features of automatic summarization?

Fri, 10 Jun 2022 02:34:23 +0000

Summarizing the meaning of documents and information
Understand the emotional meanings within the information
Provide an overview of a news item or blog post
Avoid redundancy from multiple sources
Maximize the diversity of content

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Answered: Identify any 2 stop words, frequent words and rare/valuable words from the following paragraph:

Fri, 10 Jun 2022 02:28:29 +0000

Stop words- and, for, to, be, it, in, the, that, an, can, with
Frequent words- data, involves, preprocessing, text, machines, able, puts, workable, form, work
Rare words- preparing, cleaning, analyze, highlights, features, algorithm

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Answered: Rozin is a student of class 10 AI. She wants to know the methods of evaluation. Support her with your answer.

Tue, 07 Jun 2022 01:42:48 +0000

The evaluation methods are:

Accuracy
Precision
Recall
F1 Score

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Answered: Suhas is working in a company named Krishna Enterprise as HR Head. He is facing problems from remote workers of his company. Remote workers are not able to communicate with one another seamlessly and easily...

Mon, 06 Jun 2022 04:13:09 +0000

Ans1:- The problem statement for the given situation is as follows:

Our	Remote workers and company professionals	Who?
Have a problem	Effective Communication	What?
while	remote workers work in the mines or remote area	Where?
An ideal solution would be	to provide a platform to communicate easily	Why?

Ans2:- To visualize data there are various methods, Suhas can use any of these:

1. MS Excel

2. Python Matplotlib

3. QlikView

4. Tableau

5. MS Power BI

Ans3:- Human language contains various rules based on grammatical structure. The machines need to be prepared in such a manner that can identify these rules and apply them to the model. Machines have their own rules to understand the language rules. As computer understands 0s and 1s only.

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Answered: Nowadays Google Assistant, Cortana, Siri, Alexa, etc have become an integral part of our lives. Not only can we talk to them but they also have the ability to make our lives easier.

Mon, 06 Jun 2022 04:04:49 +0000

Ans1:- Google Assistant, Cortana, Siri, Alexa

Ans2:- Virtual Assistants can assist us in various tasks. They can talk to us, keep notes of our tasks, make calls for us, and send messages. They make out lives easier by accessing our data and detecting our speech.

Ans3:- Virtual Assistants use speech recognition and try to understand the command given through speech. They detect our speech and make sense of it.

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Edited: Information overload is a real problem when we need to access a specific, important piece of information from a huge knowledge base. Automatic summarization is relevant not only for summarizing the meaning of documents and information..

Mon, 06 Jun 2022 04:02:55 +0000

Information overload is a real problem when we need to access a specific, important piece of information from a huge knowledge base. Automatic summarization is relevant not only for summarizing the meaning of documents and information, but also to understand the emotional meanings within the information, such as in collecting data from social media. Automatic summarization is especially relevant when used to provide an overview of a news item or blog post while avoiding redundancy from multiple sources and maximizing the diversity of content obtained.

For the situation given above:-

1. What do you understand by automatic summarization?

2. In which condition automatic summarization is relevant?

3. Prepare a problem statement for the given situation.

Topic	Natural Language Processing (AI Domain)
Type	Long answer type
Class	10

Answered: In which condition automatic summarization is relevant?

Mon, 06 Jun 2022 03:51:56 +0000

Automatic summarization is especially relevant when used to provide an overview of a news item or blog post while avoiding redundancy from multiple sources and maximizing the diversity of content obtained.

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Answered: How do virtual assistants work?

Mon, 06 Jun 2022 03:49:34 +0000

Virtual Assistants use speech recognition and try to understand the command given through speech. They detect our speech and make sense of it.

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Answered: Enlist the data sets used in AI modelling.

Mon, 06 Jun 2022 03:47:52 +0000

There are two types of datasets used in AI.

1. Training Data Set

2. Testing Data Set

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Answered: In a few cases, special characters are not considered as stop words and they are not removed from the corpus. Explain such a case in short.

Mon, 06 Jun 2022 02:24:55 +0000

Stopwords are the words that occur very frequently in the corpus but do not add any value to it. But few cases like e-mail ID or website URL the @ and. plays an important role. So in these cases, these symbols should be considered as either frequent words or rare words.

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Answered: List out any four chatbots along with their developer.

Mon, 06 Jun 2022 01:32:47 +0000

1. Mitsuku was created from Pandorabots AIML technology by Steve Worswick in 2005.

2. Cleverbot was created by British AI scientist Rollo Carpenter in 1997.

3. Jabberwacky was created by British programmer Rollo Carpenter in 1998.

4. Haptik was founded by Aakrit Vaish and Swapan Rajdev in August 2013.

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Which NLP applications access our data, they can help us in keeping notes of our tasks, make calls for us, send messages and a lot more? Explain this NLP application in detail.

Mon, 06 Jun 2022 01:21:59 +0000

Which NLP applications access our data, they can help us in keeping notes of our tasks, make calls for us, send messages, and a lot more? Explain this NLP application in detail.

Topic	Natural Language Processing (AI Domain)
Type	Short answer type
Class	10

Recategorized: The virtual assistants like Siri, Cortana, google assistant etc. can be taken as which type of chatbots?

Mon, 06 Jun 2022 01:21:37 +0000

Virtual assistants like Siri, Cortana, Google assistant, etc can be taken as which type of chatbots?

Topic	Natural Language Processing (AI Domain)
Type	Short answer type
Class	10

What is the aim of Natural Language Processing?

Sun, 05 Jun 2022 08:46:42 +0000

What is the aim of Natural Language Processing?

Topic	Natural Language Processing (AI Domain)
Type	Short answer type
Class	10

Shiv is learning NLP. Write one example of common syntax but no meaning for him.

Sun, 05 Jun 2022 08:39:46 +0000

Shiv is learning NLP. Write one example of common syntax but no meaning for him.

Topic	Natural Language Processing (AI Domain)
Type	Short answer type
Class	10