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: What are the key parts and facts in this article on the Athletics? Keep it to a total of five sentences. I will paste the text for your review:

Oakland A's reach deal to build stadium at Tropicana Las Vegas, per report

For the second time in a month, the Athletics have reached an agreement on a potential new stadium site in Las Vegas. According to the Nevada Independent, the A's have a deal in place with Bally's Corporation to build a "$1.5 billion stadium on a portion of the Tropicana Las Vegas site." As part of the arrangement, Bally's would demolish the Tropicana and build a new hotel-casino across from the stadium.

The A's, for their part, are slated to reduce their desired public funding bill from $500 million to $395 million by pursuing this deal instead of their previous agreement. Although that prior pact was said to be binding, it was later revealed to be contingent on the A's securing the public financing needed to proceed. The A's have yet to present Las Vegas lawmakers with a "concrete" proposal, thus delaying their clearing of that hurdle. 

The Nevada Independent's report notes that the A's intend to to begin construction on their new stadium sometime next year. That would put the stadium in line to be opened in 2027, although construction delays could push that to 2028. Should that come to pass, it would mark the completion of the A's seemingly never-ending journey to land a new ballpark.

The A's lease at the Oakland Coliseum expires after the 2024 season, suggesting that the franchise could relocate to Las Vegas before the new stadium is completed. Under such a scenario, the A's would likely play their home games at a minor-league ballpark, particularly their own Triple-A stadium in Sin City.

The A's are set to become just the second Major League Baseball team in recent times to move across state lines, joining the Montreal Expos. The Expos, of course, relocated to Washington, D.C. ahead of the 2005 season.
Response: The Oakland Athletics are building a new $1.5 billion stadium in Las Vegas on the site of the Tropicana. The property is owned by Bally's and would be razed. In this deal, the A's are requesting only $395 million in public assistance, down from the $500 million previously requested. Construction is projected to begin next year, with stadium completion projected for 2027 or 2028. The A's are expected to relocate to Las Vegas after their current stadium lease expires in 2024.

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.

Provide a clear and informative summary of the following text:

Automatic text summarization is a rapidly growing area in natural language processing, with numerous real-world applications. The goal is to develop computational models and algorithms that can analyze and condense lengthy documents into concise summaries, capturing the most essential information while preserving the overall meaning and context. There are two main paradigms in text summarization: extractive and abstractive. Extractive summarization involves identifying and extracting the most salient sentences or phrases from the original text and combining them to form the summary. This approach is relatively straightforward and can preserve the original wording and context. Abstractive summarization, on the other hand, generates entirely new sentences that convey the key ideas and information from the source text. This process often requires a deeper understanding of the semantics, context, and relationships within the text, as well as advanced natural language generation capabilities. Abstractive summaries can be more coherent and fluent, but they are also more challenging to produce accurately. Recent years have seen significant progress in text summarization, driven by advancements in deep learning and natural language processing techniques, such as attention mechanisms, transformer models, and pre-trained language models. These developments have enabled the creation of more sophisticated and accurate summarization systems capable of handling complex and diverse textual data.
user
Automatic text summarization is a growing field in natural language processing that aims to develop computational models and algorithms to condense lengthy documents into concise summaries while preserving the overall meaning and context. There are two main approaches: extractive summarization, which identifies and extracts salient sentences or phrases from the original text, and abstractive summarization, which generates new sentences conveying the key ideas and information. Abstractive summarization requires a deeper understanding of semantics, context, and language generation. Recent advancements in deep learning and natural language processing techniques, such as attention mechanisms and pre-trained language models, have enabled the creation of more sophisticated and accurate summarization systems capable of handling complex textual data.
assistant