Financial PhraseBank: Financial News Sentiment Dataset

# Financial PhraseBank - Sentiment Classification
# Based on Malo et al., JASIST 2014
# Paper: https://arxiv.org/abs/1307.5336
# Dataset: https://huggingface.co/datasets/financial_phrasebank
#
# This task classifies the sentiment of financial news sentences.
# Annotators assign both a fine-grained sentiment level (5-point scale)
# and a coarse-grained sentiment label (positive, negative, neutral)
# to each sentence from financial news articles.
#
# Fine-Grained Sentiment:
# - Strong Positive: Clear positive impact on company/market
# - Moderate Positive: Mild positive implications
# - Neutral: No sentiment or balanced positive/negative
# - Moderate Negative: Mild negative implications
# - Strong Negative: Clear negative impact on company/market
#
# Annotation Guidelines:
# 1. Read the sentence carefully in its financial context
# 2. Select the fine-grained sentiment level
# 3. Select the coarse-grained overall sentiment
# 4. Focus on investor/market perspective, not general sentiment

annotation_task_name: "Financial PhraseBank - Sentiment Classification"
task_dir: "."

data_files:
  - sample-data.json

item_properties:
  id_key: "id"
  text_key: "text"

output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

port: 8000
server_name: localhost

annotation_schemes:
  - annotation_type: select
    name: fine_grained_sentiment
    description: "Select the fine-grained sentiment level of this financial sentence"
    labels:
      - "Strong Positive"
      - "Moderate Positive"
      - "Neutral"
      - "Moderate Negative"
      - "Strong Negative"

  - annotation_type: radio
    name: overall_sentiment
    description: "What is the overall sentiment of this financial sentence?"
    labels:
      - "Positive"
      - "Negative"
      - "Neutral"
    keyboard_shortcuts:
      "Positive": "1"
      "Negative": "2"
      "Neutral": "3"
    tooltips:
      "Positive": "The sentence conveys positive financial news or outlook"
      "Negative": "The sentence conveys negative financial news or outlook"
      "Neutral": "The sentence is neutral or purely factual without sentiment"

annotation_instructions: |
  You will be shown a sentence from a financial news article. Your task is to:
  1. Determine the fine-grained sentiment (Strong Positive to Strong Negative).
  2. Assign the overall sentiment label (Positive, Negative, or Neutral).

  Important: Judge sentiment from an investor or market perspective, not general sentiment.
  For example, "layoffs" might be negative generally but could be positive for investors
  if it signals cost-cutting measures.

html_layout: |
  <div style="padding: 15px; max-width: 800px; margin: auto;">
    <div style="background: #f0f9ff; border: 1px solid #bae6fd; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
      <strong style="color: #0369a1;">Financial News Sentence:</strong>
      <p style="font-size: 16px; line-height: 1.7; margin: 8px 0 0 0;">{{text}}</p>
    </div>
  </div>

allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 2
allow_skip: true
skip_reason_required: false