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: In 2-3 sentences, summarize these paragraphs about the Shanghai Dragons.

Here are the paragraphs I'm referring to.

Around this time last year, the professional Overwatch team Shanghai Dragons had just finished up a history-making 0-40 season. At the time, nobody would have expected that just one year later they’d be leaving the league’s top three teams in a heap of black-and-blue bodies on the ground. Maybe they should change their name to the Shanghai Phoenixes.

Overwatch League season two’s third stage culminated in a mini-tournament over the weekend with hundreds of thousands of dollars on the line. Shanghai Dragons came out on top. They had the hardest possible path to this championship: They barely made it into the stage finals as the eighth seed, and then they took out the league’s three best teams—New York Excelsior, Vancouver Titans, and San Francisco Shock—back to back to back.
Response: Last season, the Shanghai Dragons finished a shockingly awful 0-40 season. This year, the Dragons just won a mini-tournament against some of the league's top teams. The Dragons entered the stage finals as the eighth seed before knocking out the Excelsior, Titans, and Shock in three straight games.

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 following text about the evaluation of text summarization systems:

Evaluating the performance and quality of text summarization systems is a crucial step in their development and deployment. Several evaluation methods and metrics are used to assess the effectiveness of summarization systems, including:

1. Human evaluation: This involves having humans manually evaluate the quality and accuracy of the generated summaries. Human evaluators assess factors like coherence, grammaticality, and informativeness of the summaries. Manual evaluation is considered the most reliable method but can be time-consuming and subjective.

2. Automatic evaluation metrics: Various automatic metrics have been developed to evaluate summarization systems, such as ROUGE (Recall-Oriented Understudy for Gisting Evaluation), which measures the overlap between the generated summary and reference summaries created by humans. Other metrics include BLEU (Bilingual Evaluation Understudy), METEOR (Metric for Evaluation of Translation with Explicit ORdering), and BERTScore, which use different approaches to compare the generated and reference summaries.

3. Task-based evaluation: This method involves evaluating the performance of summarization systems in specific real-world tasks or applications, such as information retrieval, question answering, or decision-making. The summaries are evaluated based on their effectiveness in supporting these tasks.

4. Extrinsic evaluation: This approach assesses the impact of summaries on downstream processes or applications, such as reading comprehension, information assimilation, or decision quality. Extrinsic evaluation aims to measure the practical utility of the summaries in real-world scenarios.

Evaluation methods often combine multiple approaches, such as using automatic metrics alongside human evaluation or task-based assessments, to obtain a comprehensive understanding of a summarization system's performance and identify areas for improvement.
user
The text discusses various methods and metrics used for evaluating the performance and quality of text summarization systems. These include human evaluation by manual assessments, automatic evaluation metrics like ROUGE and BLEU that measure overlap with reference summaries, task-based evaluation in specific real-world applications, and extrinsic evaluation that assesses the impact of summaries on downstream processes. A combination of these approaches is often used to comprehensively evaluate summarization systems and identify areas for improvement.
assistant