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: I want this shortened into a sentence or two:

When Mr. Lorry had finished his breakfast, he went out for a stroll on the beach. The little narrow, crooked town of Dover hid itself away from the beach, and ran its head into the chalk cliffs, like a marine ostrich. The beach was a desert of heaps of sea and stones tumbling wildly about, and the sea did what it liked, and what it liked was destruction. It thundered at the town, and thundered at the cliffs, and brought the coast down, madly. The air among the houses was of so strong a piscatory flavour that one might have supposed sick fish went up to be dipped in it, as sick people went down to be dipped in the sea. A little fishing was done in the port, and a quantity of strolling about by night, and looking seaward: particularly at those times when the tide made, and was near flood. Small tradesmen, who did no business whatever, sometimes unaccountably realised large fortunes, and it was remarkable that nobody in the neighbourhood could endure a lamplighter.

As the day declined into the afternoon, and the air, which had been at intervals clear enough to allow the French coast to be seen, became again charged with mist and vapour, Mr. Lorry’s thoughts seemed to cloud too. When it was dark, and he sat before the coffee-room fire, awaiting his dinner as he had awaited his breakfast, his mind was busily digging, digging, digging, in the live red coals.
Response: After his breakfast, Mr. Lorry went for a walk on the beach. He seemed troubled later on when he was waiting for his dinner.

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.

Summarize the following passage: Automatic text summarization is a challenging task in natural language processing (NLP) that involves generating a concise and coherent summary of a given text document or set of documents. The goal is to distill the most important information and key points while preserving the overall meaning and context. This process is particularly useful for dealing with large volumes of textual data, as it allows users to quickly grasp the essence of the content without having to read through the entire text. There are two main approaches to automatic 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, involves generating entirely new sentences that capture the essence of the text, often by using advanced language generation techniques. Both approaches have their advantages and challenges, and the choice between them depends on factors such as the domain, the available data, and the desired level of human-like summarization.
user
Automatic text summarization is a challenging NLP task that aims to generate concise and coherent summaries of given text documents. The goal is to distill the most important information while preserving meaning and context. There are two main approaches: extractive summarization, which selects and concatenates relevant sentences, and abstractive summarization, which generates new sentences capturing the essence of the text. The choice between these approaches depends on factors like domain, available data, and desired level of human-like summarization.
assistant