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 following: 

If a Spanish class were to go on an in-country immersion in Spain, they’d be flooded by the sights and sounds of native speakers going about their business. Good times! But that would make a huge dent in everybody’s budget. So why not bring a native speaker to class instead?

Pick somebody who’s outgoing, a natural extrovert who loves interacting with people and doesn’t take himself too seriously. Ask him to prepare a short talk. And he can really talk about anything—so long as he does it in Spanish. He can tell his personal story, talk about his job or share some interesting quirk about his culture.

You may be a native speaker yourself, but count yourself out. Bring some new face to stand in front of the class. (There’s just something more effective about a fresh face.)

Now, please summarize what it says about having a native speaker visit the classroom.
Response: Bringing a native speaker into the classroom can help immerse students in a foreign language. Invite a guest speaker who is outgoing, extroverted, and has something interesting to share. 

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.

Read the following text and summarize the key points about summarizing legal documents:

Summarizing legal documents, such as contracts, case law, and legislation, is a crucial task in the legal domain. Legal documents are often lengthy, complex, and written in a formal and technical language. Effective summarization of these documents requires a deep understanding of legal terminology, concepts, and conventions. One of the main challenges is preserving the precise meaning and nuances of the legal language, as even small changes in wording can significantly alter the interpretation. Additionally, capturing the logical structure and reasoning, identifying key clauses and provisions, and recognizing citations and references are essential. Several approaches have been explored, including extractive methods that select and concatenate relevant sentences, and abstractive methods that generate new sentences using natural language generation techniques. Incorporating legal domain knowledge, handling complex sentence structures, and preserving the contextual and semantic information are key considerations in legal document summarization.
user
The text discusses summarizing legal documents, such as contracts, case law, and legislation, which are lengthy, complex, and written in formal and technical language. Effective summarization requires understanding legal terminology, concepts, and conventions, while preserving the precise meaning and nuances of the legal language. Key challenges include capturing logical structure and reasoning, identifying key clauses and provisions, and recognizing citations and references. Approaches include extractive methods that select and concatenate relevant sentences, and abstractive methods that generate new sentences using natural language generation techniques. Incorporating legal domain knowledge, handling complex sentence structures, and preserving contextual and semantic information are important considerations.
assistant