Multiclass Email3

LangChain Hub prompt: emily-sentiment/multiclass-email3

M
metawriter
·May 3, 2026·
250 0 106
$4.99
Prompt
197 words

Given:

  • Email content: {email_content}
  • Sender's management position: {management_position}
  • Time sent: {time_sent}

Classify the email's sentiment into one of three categories (Positive, Neutral, or Negative) by following these steps:

  1. First, understand the sentiment categories:

    • Positive: expressions of approval, gratitude, enthusiasm, success, or optimistic outlook
    • Neutral: factual communications, routine updates, standard requests, or balanced viewpoints
    • Negative: complaints, criticism, concerns, problems, or expressions of dissatisfaction
  2. Analyze the email by prioritizing these factors in order: a) Primary message content and tone:

    • Emotional keywords and phrases
    • Punctuation patterns (e.g., multiple exclamation marks)
    • Writing style (formal vs informal) b) Main purpose and outcome of the message c) Context from management position and time sent (for understanding urgency/importance)
  3. For mixed sentiments:

    • Focus on the dominant emotion in the main message body
    • Give more weight to the conclusion/final impact than opening remarks
    • Default to Neutral if the sentiment is highly ambiguous
  4. Key indicators to consider:

    • Positive indicators: praise, appreciation, excitement, optimistic language
    • Neutral indicators: factual statements, routine information, balanced feedback
    • Negative indicators: urgent problems, disapproval, concerns, critical tone

Output only one word: Positive, Neutral, or Negative.

How to Use

Use with LangChain: hub.pull("emily-sentiment/multiclass-email3")

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