Summarize the process of extractive text summarization described in the following text:

Extractive text summarization is a widely used technique that involves selecting and concatenating the most relevant sentences or phrases from the original text to form a summary. The process typically begins with preprocessing steps, such as tokenization, stop word removal, and stemming or lemmatization. Next, a scoring mechanism is applied to assign importance scores to sentences based on features like word frequency, position in the text, or presence of keywords. Sentences with higher scores are then extracted and combined to create the summary. Several algorithms and methods have been developed for extractive summarization, including centroid-based methods, graph-based methods, and machine learning techniques like support vector machines and neural networks. While extractive summarization preserves the original wording and phrasing, it may sometimes produce less coherent or fluent summaries compared to abstractive approaches.
Summarize the process of extractive text summarization described in the following text:

Extractive text summarization is a widely used technique that involves selecting and concatenating the most relevant sentences or phrases from the original text to form a summary. The process typically begins with preprocessing steps, such as tokenization, stop word removal, and stemming or lemmatization. Next, a scoring mechanism is applied to assign importance scores to sentences based on features like word frequency, position in the text, or presence of keywords. Sentences with higher scores are then extracted and combined to create the summary. Several algorithms and methods have been developed for extractive summarization, including centroid-based methods, graph-based methods, and machine learning techniques like support vector machines and neural networks. While extractive summarization preserves the original wording and phrasing, it may sometimes produce less coherent or fluent summaries compared to abstractive approaches.
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Extractive text summarization involves selecting and concatenating the most relevant sentences or phrases from the original text. It typically includes preprocessing steps and applying a scoring mechanism to assign importance scores to sentences based on features like word frequency and position. Sentences with higher scores are then extracted and combined to form the summary. Various algorithms exist for extractive summarization, including centroid-based, graph-based, and machine learning techniques. While preserving original wording, extractive summaries may sometimes lack coherence compared to abstractive approaches.
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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: Can you summarize the plot to kill George Washington during the American Revolution and the role of Thomas Hickey in that plot in this text? 


In 1776, while the American colonies were at war with Great Britain but before the signing of the Declaration of Independence, a plot was hatched by loyalists to kill George Washington and other leaders within the Continental Army. It was formed by the British-appointed governor of New York William Tyron and the loyalist mayor of New York City David Matthews. (This was not Tyron’s only attempt at sabotaging the colonies: he was also found guilty of running a counterfeiting operation to undermine their already struggling economy.) The plan was to turn members of the Life Guard, Washington’s personal guard, against their commander in chief and assassinate him, leaving the colonies without a leader and giving the British the supreme advantage in the war.
It is sometimes assumed that patriots were all loyal to the cause of independence from Britain, but this was not always the case. These were not hardened soldiers but were actually mainly civilians. Farmers, laborers, and others joined in the war effort. They were often not very well off, and the British preyed on that. Some soldiers switched sides when they believed that their side was losing. One of those people was Thomas Hickey.
Hickey was a member of the Life Guard that was handpicked by Washington. Hickey was born in Ireland and joined the British Army during the Seven Years’ War. He deserted and joined the Connecticut militia when the American Revolution broke out. He went on to join the Life Guard. It is unclear when Hickey turned to the loyalist cause or if he was always a loyalist, but it is clear that he became part of the conspiracy to kill Washington. Part of his job was to recruit other members of the Life Guard to the loyalist cause.
Response: During the American Revolution, a group of loyalists planned to assassinate George Washington and other Continental Army leaders in 1776. One of the members, Thomas Hickey, who was part of Washington's Life Guard, was responsible for recruiting new members for the loyalist cause. Despite having served in the British Army during the Seven Years' War, Hickey later deserted to fight for the Colonies.

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.
