Emotion Cause Extraction (RECCON)

# Emotion Cause Extraction (RECCON)
# Based on Poria et al., EMNLP 2020
# Paper: https://aclanthology.org/2020.emnlp-main.431/
# Dataset: https://github.com/declare-lab/RECCON
#
# RECCON focuses on recognizing emotion causes in conversations.
# For each utterance expressing an emotion, annotators identify:
# 1. The emotion being expressed
# 2. Which prior utterance(s) contain the cause
# 3. The specific span within those utterances that is causal
#
# Cause Types:
# - Self-contagion: Cause is in the same speaker's prior utterance
# - Inter-personal: Cause is in another speaker's utterance
# - No explicit cause: Emotion has no identifiable textual cause
#
# Annotation Guidelines:
# 1. First identify the target emotion in the highlighted utterance
# 2. Look backwards in the conversation for potential causes
# 3. Mark specific spans that directly trigger the emotion
# 4. A cause must be NECESSARY for the emotion (counterfactual test)
# 5. Multiple causes can exist for a single emotion

port: 8000
server_name: localhost
task_name: "Emotion Cause Extraction"

data_files:
  - sample-data.json
id_key: id
text_key: dialogue

output_file: annotations.json

annotation_schemes:
  # Step 1: Identify the emotion in the target utterance
  - annotation_type: radio
    name: emotion
    description: "What emotion is expressed in the highlighted (last) utterance?"
    labels:
      - "Happiness"
      - "Sadness"
      - "Anger"
      - "Fear"
      - "Surprise"
      - "Disgust"
      - "Neutral"
    tooltips:
      "Happiness": "Joy, excitement, contentment, satisfaction, amusement"
      "Sadness": "Sorrow, disappointment, grief, melancholy"
      "Anger": "Frustration, irritation, annoyance, rage"
      "Fear": "Anxiety, worry, nervousness, terror"
      "Surprise": "Astonishment, amazement, shock (positive or negative)"
      "Disgust": "Revulsion, disapproval, contempt"
      "Neutral": "No clear emotion expressed"

  # Step 2: Identify cause location
  - annotation_type: radio
    name: cause_type
    description: "Where is the cause of this emotion located?"
    labels:
      - "In speaker's own prior utterance"
      - "In other speaker's utterance"
      - "In multiple utterances"
      - "No explicit cause in text"
    tooltips:
      "In speaker's own prior utterance": "Self-contagion: the speaker's earlier words triggered their current emotion"
      "In other speaker's utterance": "Inter-personal: another speaker's words triggered this emotion"
      "In multiple utterances": "The cause spans multiple prior utterances"
      "No explicit cause in text": "The emotion has no identifiable textual cause in the conversation"

  # Step 3: Mark causal spans
  - annotation_type: span
    name: causal_spans
    description: "Highlight the specific text spans that CAUSED the emotion"
    labels:
      - "Cause"
    label_colors:
      "Cause": "#ef4444"
    tooltips:
      "Cause": "The specific words/phrases that directly triggered the emotion (necessary condition)"
    allow_overlapping: false

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