SemEval-2017 Task 4 - Sentiment Multi-Rating

# SemEval-2017 Task 4 - Sentiment Multi-Rating
# Based on Rosenthal et al., SemEval 2017
# Paper: https://aclanthology.org/S17-2088/
# Dataset: http://alt.qcri.org/semeval2017/task4/
#
# This task asks annotators to rate tweets on multiple sentiment dimensions
# using a multi-rate scheme, and to assign an overall sentiment label.
# The multirate scheme allows rating the same text on sentiment intensity,
# subjectivity, and emotion strength simultaneously.
#
# Sentiment Labels:
# - Very Negative, Negative, Neutral, Positive, Very Positive
#
# Rating Dimensions:
# - Sentiment Intensity: How strong is the sentiment expressed?
# - Subjectivity: How subjective vs objective is the text?
# - Emotion Strength: How emotionally charged is the text?
#
# Annotation Guidelines:
# 1. Read the tweet carefully
# 2. Rate each dimension using the 5-point scale
# 3. Select the overall sentiment label

annotation_task_name: "SemEval-2017 Task 4 - Sentiment Multi-Rating"
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: multirate
    name: sentiment_dimensions
    description: "Rate the tweet on multiple sentiment dimensions"
    labels:
      - "Very Negative"
      - "Negative"
      - "Neutral"
      - "Positive"
      - "Very Positive"
    options:
      - "Sentiment Intensity"
      - "Subjectivity"
      - "Emotion Strength"

  - annotation_type: radio
    name: overall_sentiment
    description: "What is the overall sentiment of this tweet?"
    labels:
      - "Positive"
      - "Negative"
      - "Neutral"
    keyboard_shortcuts:
      "Positive": "1"
      "Negative": "2"
      "Neutral": "3"
    tooltips:
      "Positive": "The tweet expresses a positive opinion or emotion"
      "Negative": "The tweet expresses a negative opinion or emotion"
      "Neutral": "The tweet is neutral, factual, or does not express clear sentiment"

annotation_instructions: |
  You will be shown a tweet. Your task is to:
  1. Rate the tweet on three dimensions using the 5-point scale:
     - Sentiment Intensity: How strongly positive or negative is the sentiment?
     - Subjectivity: How subjective (opinion-based) vs. objective (fact-based) is the text?
     - Emotion Strength: How emotionally charged is the language used?
  2. Select the overall sentiment label: Positive, Negative, or Neutral.

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;">Tweet:</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