Read the following text carefully:

Automatic text summarization is a challenging task in natural language processing (NLP) that involves generating concise and coherent summaries of lengthy documents or text sources. The primary objective of text summarization is to distill the essential information from a source text while preserving its overall meaning and context.

There are two main approaches to text summarization: extractive and abstractive. Extractive summarization involves selecting and concatenating the most relevant sentences or phrases from the original text to form the summary. Abstractive summarization, on the other hand, aims to generate entirely new sentences that capture the essence of the text, often employing advanced language generation models.

Text summarization algorithms rely on various NLP techniques, such as topic modeling, semantic analysis, sentence scoring, and graph-based ranking. These techniques help identify the most salient information, determine the relevance of sentences or phrases, and organize the summary in a coherent and fluent manner.

Summarize the given text in approximately 60 words.
Read the following text carefully:

Automatic text summarization is a challenging task in natural language processing (NLP) that involves generating concise and coherent summaries of lengthy documents or text sources. The primary objective of text summarization is to distill the essential information from a source text while preserving its overall meaning and context.

There are two main approaches to text summarization: extractive and abstractive. Extractive summarization involves selecting and concatenating the most relevant sentences or phrases from the original text to form the summary. Abstractive summarization, on the other hand, aims to generate entirely new sentences that capture the essence of the text, often employing advanced language generation models.

Text summarization algorithms rely on various NLP techniques, such as topic modeling, semantic analysis, sentence scoring, and graph-based ranking. These techniques help identify the most salient information, determine the relevance of sentences or phrases, and organize the summary in a coherent and fluent manner.

Summarize the given text in approximately 60 words.
user
Automatic text summarization is an NLP task that generates concise summaries from lengthy texts, preserving essential information and meaning. It employs two approaches: extractive (selecting relevant sentences) and abstractive (generating new sentences). Algorithms utilize techniques like topic modeling, semantic analysis, and sentence scoring to identify salient information and construct coherent summaries.
assistant
Generate a series of (instruction, response) pairs that are similar in context and structure to the example provided below. Each pair should consist of a concise instruction followed by an appropriate, detailed response. The instruction should pose a clear task or question, while the response should provide a comprehensive answer or solution that could be understood by someone with a basic understanding of the subject.

Example pair: 
Instruction: Read the article below:

Middle-of-funnel content

At this next stage, your target audience is now aware of your business and the solution you provide, and they’re interested.

They trust you enough to make slightly bigger commitments, like signing up for a webinar and engaging with longer-form content; and they’re interested enough in your offering to read brand-specific material like case studies, testimonials, and newsletter emails.

Their goal is to learn more about the solution you provide—both in general and the one specifically offered by your business.

Your goal is to educate them on your offering and set your business apart from competitors—not just with your features and benefits but with your expertise and knowledge.

Next, write a summary of what it says about Middle-of-funnel content
Response: Middle-of-funnel content includes brand-specific content that educates interested audiences that are already considering an offer.

Your task is to generate more pairs that maintain this level of clarity and detail. The topic is Summarization. Write a long text of instruction by yourself, then summarize the given instruction in a response. Ensure that the responses are informative and accurate, suitable for an educational context. 

Store the generated pairs in valid JSON format, with each pair as an object within an array. Each object should have two key-value pairs: "instruction" and "response". For instance: 

{"contents": [{"instruction": "text", "response": "text"}, {"instruction": "text", "response": "text"}, ...]} 

Remember to maintain consistency in the format and ensure the generated pairs are diverse and cover a broad range of subjects. You must return the response in the asked format and you must not add any additional text in your response.
