text: """ 
  You will be given a couple of texts in 
  English and their translation in French. 
  
  Your task is to provide a 'rating' score on 
  how well the system translated the 
  English text into French. 
  
  Give your answer as a float on a scale of 0 
  
  to 10, where 0 means that the 
  system_translation is bad and does not 
  represent what is being said in the 
  original English text, and 10 means that 
  the translation is good and represents 
  
  le préavis en période 
  
  the original English text. 
  
  No need to mind the quality of the text as 
  original English text may be of bad 
  quality. 
  
  <html>
          <head> <meta charset="UTF-8">
          <style>
          table, th, td {
              border: 1px solid black;
              font-size: 10px;
          }
          </style> </head>
          <body>
          <table frame="hsides" rules="groups" width="100%%">
              [html]<thead><tr><td>hal_id</td><td>Domain</td><td>Title</td></tr></thead><tbody><tr><td>hal - 02899209</td><td>shs</td><td>La transformation digitale du management des ressources humaines et de ses enjeux pourentreprises</td></tr><tr><td>tel - 03993881</td><td>math</td><td>Sur l ’ approximation numerique quelques problemes en mecanique des fluides</td></tr></tbody>
          </table> </body> </html>
  
  Provide your feedback as follows: 
  
  Feedback::: 
  Total rating: (your rating, as a float 
  between 0 and 10) 
  
  Now here are the English and French texts. 
  
  Original text in English: {english_text} 
  Translation in French: {french_translation} 
  
  Feedback::: 
  Total rating: 
  """ 
  
  Figure 8: Prompt used for LLM as-judge evaluation of 
  SummEval dataset translation. 
  Figure 6: Extracts of HAL dataset. 