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: Summarize the following article in a few sentences. 
Mexico’s army welcomed a new search puppy on Wednesday, gifted from Turkey following the death of a Mexican rescue dog who had been helping to find survivors of February’s massive earthquake near the Syrian border.
The 3-month-old German Shepherd will join Mexico’s famed canine unit, specialized in helping locate survivors in a country prone to earthquakes and other natural disasters.
The black and beige canine with perky ears and outsize paws has been named “Arkadas” – meaning “friend” in Turkish – following an online vote.
Arkadas will be trained by the same trainer who cared for Proteo, the rescue dog that died on mission in Turkey, the army said.
Mexico deployed rescue dogs to Turkey after the magnitude 7.8 earthquake shook a huge area near the southern border with Syria, causing at least 54,000 deaths across both nations.
Mexico paid homage to Proteo, also a German Shepherd, at a military funeral earlier this year.
Wearing a padded green harness featuring a tiny Mexican flag, Arkadas was welcomed to the force in a formal ceremony at a military base in Mexico City on Wednesday, joined by his new canine and human colleagues, standing to attention.
The excitable pup barked as Mexico’s national anthem blared out from speakers.
“Thanks to my friends from Mexico who welcomed me with great affection, I promise to do my best to be a great search and rescue dog,” the Mexican defense ministry tweeted on behalf of Arkadas.
Response: On Wednesday, Turkey gifted Mexico's army a 3-month-old German Shepherd after the death of a Mexican rescue dog that was on a mission to find survivors of Fedurary's massive earthquake. After an online vote, the new search puppy has been named "Arkadas" which means "friend" in Turkish. Arkadas will be trained by the same trainer who took care of the rescue dog that died while on a mission in Turkey. The Mexican army has paid homage to the fallen rescue dog with a military funeral and has welcomed the new rescue puppy with a formal ceremony. 

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:

Evaluating the quality of text summaries is a crucial aspect of summarization systems and algorithms. Several evaluation metrics have been developed to assess the effectiveness and performance of summarization techniques. One commonly used metric is ROUGE (Recall-Oriented Understudy for Gisting Evaluation), which measures the overlap between the generated summary and one or more reference summaries created by human experts. ROUGE calculates various scores, such as ROUGE-N (N-gram overlap), ROUGE-L (longest common subsequence), and ROUGE-SU (skip-gram overlap), providing insights into the quality of the summary in terms of content coverage and linguistic similarity. Other evaluation metrics include pyramid scoring, which assesses the inclusion of key information units in the summary, and readability measures that analyze the coherence, grammaticality, and overall fluency of the generated text.
user
Evaluating the quality of text summaries is crucial, and several evaluation metrics have been developed for this purpose. ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is a commonly used metric that measures the overlap between the generated summary and reference summaries created by human experts, calculating scores like ROUGE-N, ROUGE-L, and ROUGE-SU. Other metrics include pyramid scoring, which assesses the inclusion of key information units, and readability measures that analyze the coherence, grammaticality, and overall fluency of the generated text.
assistant