DimABSA: Dimensional Aspect-Based Sentiment Analysis

# DimABSA: Dimensional Aspect-Based Sentiment Analysis
# Based on Yu et al., SemEval-2026 Task 3
# Paper: https://aclanthology.org/2026.semeval-1.452/
# Task/dataset: https://github.com/DimABSA/DimABSA2026
#
# DimABSA replaces categorical polarity (positive/negative/neutral) with
# continuous valence-arousal (VA) ratings. Track A (DimABSA) has three
# subtasks over consumer reviews: (1) dimensional aspect sentiment
# regression, (2) triplet extraction (aspect, opinion, VA), and (3)
# quadruplet extraction (aspect, category, opinion, VA). Track B
# (DimStance) reformulates stance detection as VA regression over stance
# targets. This showcase models the core annotation: mark the aspect term
# and its opinion term, then rate valence and arousal.
#
# Valence: how pleasant/positive the sentiment is (1 = very negative,
#          9 = very positive; 5 = neutral).
# Arousal: how active/intense the sentiment is (1 = very calm,
#          9 = very excited/intense).

annotation_task_name: "DimABSA - Dimensional Aspect Sentiment"
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: span
    name: aspect_term
    description: "Highlight the aspect term (the entity or feature being evaluated)"
    labels:
      - "Aspect"

  - annotation_type: span
    name: opinion_term
    description: "Highlight the opinion term expressing sentiment toward the aspect"
    labels:
      - "Opinion"

  - annotation_type: slider
    name: valence
    description: "Valence of the sentiment toward this aspect (1 = very negative, 5 = neutral, 9 = very positive)"
    min_value: 1
    max_value: 9

  - annotation_type: slider
    name: arousal
    description: "Arousal of the sentiment toward this aspect (1 = very calm, 9 = very intense)"
    min_value: 1
    max_value: 9

  - annotation_type: text
    name: aspect_category
    description: "Aspect category (for the quadruplet setting, e.g. FOOD#QUALITY) - optional"
    textarea: false
    required: false

annotation_instructions: |
  Read the sentence. Highlight each aspect term (what is being evaluated)
  and the opinion term expressing sentiment about it. Then rate the
  sentiment on two continuous dimensions: valence (how positive/negative)
  and arousal (how calm/intense). Optionally record the aspect category.

html_layout: |
  <div style="padding: 15px; max-width: 820px; margin: auto;">
    <div style="background: #f5f3ff; border: 1px solid #ddd6fe; border-radius: 8px; padding: 16px; margin-bottom: 12px;">
      <strong style="color: #5b21b6;">Sentence:</strong>
      <p style="font-size: 17px; line-height: 1.7; margin: 8px 0 0 0;">{{text}}</p>
    </div>
  </div>

allow_all_users: true
instances_per_annotator: 40
annotation_per_instance: 3
allow_skip: true