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.

Summarize the following text about the different types of text summarization:

Text summarization can be categorized into two main types: extractive and abstractive. Extractive summarization involves selecting and concatenating the most important sentences or phrases from the original text to form the summary. This approach retains the original wording and phrasing of the source text. In contrast, abstractive summarization generates entirely new sentences that capture the essence of the text, often rephrasing and paraphrasing the content. Abstractive summaries are more like human-written summaries but are more challenging to produce computationally. Recent advances in natural language processing and deep learning have enabled the development of more sophisticated abstractive summarization models.
user
There are two main types of text summarization: extractive and abstractive. Extractive summarization selects and concatenates important sentences from the original text, retaining its wording. Abstractive summarization generates new sentences that capture the text's essence, rephrasing and paraphrasing the content. Abstractive summaries are more human-like but computationally challenging. Recent advancements in NLP and deep learning have enabled better abstractive summarization models.
assistant