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: Please summarize how Asian American and Pacific Islander Heritage Month was started based on the text below: 

History
A former congressional staffer in the 1970s, Jeanie Jew, first approached Representative Frank Horton with the idea of designating a month to recognize Asian Pacific Americans, following the bicentennial celebrations.[19] In June 1977, Representatives Horton, and Norman Y. Mineta, introduced a United States House of Representatives resolution to proclaim the first ten days of May as Asian-Pacific Heritage Week.[20][21] A similar bill was introduced in the Senate a month later by Daniel Inouye and Spark Matsunaga.[20][22]

The proposed resolutions sought that May be designated for two reasons. For on May 7, 1843, the first Japanese immigrant arrived in the United States.[23][24][25] More than two decades later, on May 10, 1869, the golden spike was driven into the first transcontinental railroad, which was completed using Chinese labor.[23][24][26]

President Jimmy Carter signed a joint resolution for the celebration on October 5, 1978.[20]

On May 1, 2009, President Barack Obama signed Proclamation 8369, recognizing the month of May as Asian American and Pacific Islander Heritage Month.[1][27]
Response: A former congressional staffer with the idea approached a representative about it in the 1970s. In 1977, a resolution was introduced in the House and the Senate, and the President signed it in 1978. However, that resolution was only for the first ten days of May. It wasn't until 2009 that the whole month of May was named Asian American and Pacific Islander Heritage Month.

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 main ideas behind abstractive text summarization techniques from the following passage:

Abstractive text summarization aims to produce a concise summary that captures the key points of the source text in a more human-like way, often involving paraphrasing or generating entirely new sentences. Unlike extractive methods which simply select existing sentences, abstractive techniques rely on advanced natural language processing and generation models. Common approaches include:

- Sequence-to-sequence models: Neural networks that take the source text as input and generate the summary as output, learning to paraphrase and compress the content.

- Graph-based methods: Represent the text as semantic graphs of concepts and relations, then apply graph algorithms to identify salient information to include in the summary.

- Topic modeling: Discover the underlying topics in the text, then generate summaries focused on the core topics.

- Abstractive summarization is challenging due to the need to deeply understand context and meaning, but can produce more coherent and concise summaries compared to purely extractive methods.
user
Abstractive text summarization techniques aim to generate human-like summaries by paraphrasing and rephrasing the key ideas from the source text. Common approaches include sequence-to-sequence models that learn to compress and rephrase, graph-based methods that extract concepts and relations, topic modeling to identify core topics, and other advanced natural language processing techniques. Abstractive methods are challenging but can produce more coherent and concise summaries compared to extractive techniques.
assistant