# Generated by utils.py
dataset_name: tir
doc_to_text: "You are tasked with performing sentiment classification on the following\
  \ Tigrinya text. For each input, classify the sentiment as positive, negative, or\
  \ neutral. Use the following guidelines: \n\n Positive: The text expresses happiness,\
  \ satisfaction, or optimism. \nNegative: The text conveys disappointment, dissatisfaction,\
  \ or pessimism. \nNeutral: The text is factual, objective, or without strong emotional\
  \ undertones. \n\nIf the text contains both positive and negative sentiments, choose\
  \ the dominant sentiment. For ambiguous or unclear sentiments, select the label\
  \ that best reflects the overall tone. Please provide a single classification for\
  \ each input.\n\ntext: {{tweet}} \nlabel: "
include: afrisenti
task: afrisenti_tir_prompt_5
