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: Tell me in a sentence or two what this text says about Nirvana.

Nirvana was an American rock band formed in Aberdeen, Washington, in 1987. Founded by lead singer and guitarist Kurt Cobain and bassist Krist Novoselic, the band went through a succession of drummers, most notably Chad Channing, and then recruited Dave Grohl in 1990. Nirvana's success popularized alternative rock, and they were often referenced as the figurehead band of Generation X. Their music maintains a popular following and continues to influence modern rock culture.
Response: Nirvana was a Washington-based rock band formed in 1987 by Kurt Cobain and Krist Novoselic, with Chad Channing and Dave Grohl being the most notable drummers. They are often cited as an influencer of modern rock culture.

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.

Discuss the role of topic modeling and lexical chains in text summarization, and how they can be leveraged to improve the accuracy and coherence of generated summaries.
user
Topic modeling techniques like Latent Dirichlet Allocation (LDA) can be used to identify the central topics or themes discussed in a given text. This information can guide the summarization process by prioritizing sentences or passages that are most relevant to the key topics. Lexical chains refer to the linking of related words and concepts throughout a text. Analyzing lexical chains can help capture the main ideas, identify key entities and relationships, and maintain coherence in the generated summary by including sentences that cover the important concepts and their connections. Both topic modeling and lexical chain analysis can enhance the accuracy and coherence of summaries by ensuring that the most salient and interconnected content is preserved.
assistant