Emotion Discovery and Reasoning its Flip
Emotion discovery and flip reasoning task requiring annotators to identify the current emotion in a dialogue turn, and locate trigger spans and flip points where emotions change. Based on SemEval-2024 Task 10.
Configuration Fileconfig.yaml
# Emotion Discovery and Reasoning its Flip
# Based on Kumar et al., SemEval 2024
# Paper: https://aclanthology.org/volumes/2024.semeval-1/
# Dataset: https://github.com/SemEval/semeval-2024-task10
#
# This task asks annotators to identify the emotion expressed in a dialogue
# turn, and to highlight the trigger spans that cause the emotion as well
# as any points where the emotion changes (flips) from the previous state.
annotation_task_name: "Emotion Discovery and Reasoning its Flip"
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: radio
name: current_emotion
description: "What emotion is expressed in this dialogue turn?"
labels:
- "Joy"
- "Sadness"
- "Anger"
- "Fear"
- "Surprise"
- "Disgust"
- "Neutral"
keyboard_shortcuts:
"Joy": "1"
"Sadness": "2"
"Anger": "3"
"Fear": "4"
"Surprise": "5"
"Disgust": "6"
"Neutral": "7"
tooltips:
"Joy": "Happiness, excitement, delight, or amusement"
"Sadness": "Grief, sorrow, disappointment, or loss"
"Anger": "Frustration, irritation, rage, or hostility"
"Fear": "Anxiety, worry, dread, or apprehension"
"Surprise": "Astonishment, shock, or unexpectedness"
"Disgust": "Revulsion, contempt, or strong disapproval"
"Neutral": "No clear emotional expression"
- annotation_type: span
name: emotion_triggers
description: "Highlight the trigger that caused the emotion and the point where it changed."
labels:
- "Emotion Trigger"
- "Emotion Flip Point"
annotation_instructions: |
You will be shown a dialogue turn with context about the speaker and their previous emotion. Your task is to:
1. Read the dialogue turn and the context carefully.
2. Identify the current emotion expressed by the speaker.
3. Highlight the span(s) that triggered the emotion.
4. If the emotion changed from the previous state, highlight the flip point.
html_layout: |
<div style="padding: 15px; max-width: 800px; margin: auto;">
<div style="background: #eff6ff; border: 1px solid #bfdbfe; border-radius: 8px; padding: 12px; margin-bottom: 12px;">
<strong style="color: #1e40af;">Speaker:</strong> <span>{{speaker}}</span>
|
<strong style="color: #1e40af;">Previous Emotion:</strong> <span>{{previous_emotion}}</span>
</div>
<div style="background: #f0f9ff; border: 1px solid #bae6fd; border-radius: 8px; padding: 16px; margin-bottom: 16px;">
<strong style="color: #0369a1;">Dialogue Turn:</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
Sample Datasample-data.json
[
{
"id": "emoflip_001",
"text": "Wait, are you serious? They actually gave me the lead role? I was sure they would pick someone else! This is unbelievable!",
"speaker": "Emma",
"previous_emotion": "Neutral"
},
{
"id": "emoflip_002",
"text": "I just found out that my flight got cancelled and there are no alternatives until tomorrow. I had promised my daughter I would be there for her recital tonight.",
"speaker": "Robert",
"previous_emotion": "Joy"
}
]
// ... and 8 more itemsGet This Design
Clone or download from the repository
Quick start:
git clone https://github.com/davidjurgens/potato-showcase.git cd potato-showcase/semeval/2024/task10-emotion-flip potato start config.yaml
Details
Annotation Types
Domain
Use Cases
Tags
Found an issue or want to improve this design?
Open an IssueRelated Designs
Character Identification on Multiparty Dialogues
Identification and linking of character mentions in TV show dialogue, combining span annotation with entity resolution for the main cast of Friends. Based on SemEval-2018 Task 4.
Multimodal Emotion Cause Analysis
Multimodal emotion cause analysis in conversations, requiring annotators to identify emotion expressions and their causal utterances in dialogue, and classify the emotion type. Based on SemEval-2024 Task 3.
Aspect-Based Sentiment Analysis
Identification of aspect terms in review text with sentiment polarity classification for each aspect. Based on SemEval-2016 Task 5 (ABSA).