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: Write a short summary of the passage.

This is the passage:
The most famous description of Valhalla in Old Norse literature, that of Grímnismál, portrays it as being located in Asgard, the gods’ celestial fortress.

However, other lines of evidence suggest that it was at least sometimes seen as being located underground, like the more general underworld.
Response: Grímnismál is the most famous portrayal of Valhalla, locating it in Asgard, but other theories say it was underground.

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.

Write a detailed summary of the following text, identifying the main ideas and key supporting details:

Summarization is the process of producing a concise and accurate synthesis of one or more text documents, capturing the major information from the original texts while significantly reducing the amount of text. It serves to highlight the essential ideas and remove redundant information, thereby making the text easier to digest and process. There are two main types of summarization: extractive and abstractive. Extractive summarization involves selecting and concatenating the most important sentences or passages from the source text(s) to form the summary. Abstractive summarization, on the other hand, aims to paraphrase and rewrite the content using different words and sentence structures, thereby generating an entirely new text that captures the essence of the original. Summarization algorithms often employ techniques from Natural Language Processing (NLP) and Machine Learning (ML) to analyze the semantic content, identify key concepts, and determine the relative importance of different text segments.
user
This text explains the summarization process, which involves condensing one or more texts into a concise synthesis. It identifies the main purposes as highlighting essential ideas and removing redundancies. Two main types are outlined: extractive summarization, where key sentences are selected and concatenated; and abstractive summarization, where the content is rewritten using different words. The text notes that summarization algorithms employ NLP and ML techniques to analyze semantics, identify key concepts, and determine the importance of text segments.
assistant