ML-ESG Compliance Report

ESG Compliance Report - Chinese Dataset Annotation Task

NTCIR-19 2025-2026 International Research Project

ACTIVITY INTRODUCTION

We plan to participate in the ML-ESG Compliance Report Chinese dataset annotation task, which is an international collaborative research project aimed at advancing ESG automated detection technology.

Participating Teams: Japanese Team, National Taiwan University, National Taipei University
Project Duration: March 1, 2025 - May 31, 2025 (90-day annotation period)

Why is ESG Compliance Important?

  • 69% of investment companies have incorporated ESG standards into their regulatory compliance strategies
  • Among the top 250 global companies, 96% have conducted ESG reporting
  • In 2022, 86% of global asset managers have integrated sustainable investing into their investment strategies
  • 97% of asset managers in the Asia-Pacific region have adopted ESG strategies

Three Major Global ESG Trends

ESG Integration into Corporate Operations

More companies are incorporating ESG principles into their daily operations

Climate Change Response

Companies are adopting more proactive environmental measures to address global warming

Increasingly Strict Regulatory Framework

Governments and international organizations continue to strengthen ESG regulations

PROJECT TIMELINE

2025/02/26 (Wed) 20:30-21:00

First Online Discussion Meeting - ML-ESG CR 2026

2025/03/01 - 2025/05/31 (90 Days)

Data Annotation Phase - ESG reporting standards and data annotation work

2025/06 - 2025/07

Complete ESG report annotation and establish precise ESG data models

2026/12

Participate in NTCIR-19 International Conference and present research findings

DATA LABELING PROCESS

Step Task Description
Step 1 Confirm ESG Indicator Location Confirm the pages where ESG indicators appear
Step 2 Indicator Classification Quantitative data (numbers, percentages) or discussion/analysis (text description)
Step 3 Unit Verification Percentage (%), currency ($), text description, or other data types
Step 4 Compliance Confirmation Ensure ESG reports comply with regulatory requirements

MULTI-LANGUAGE SUPPORT

English

Juyeon

French

Juyeon

Korean

Hanwool

Chinese

Prof. Day (NTPU Team)

Japanese

Prof. Seki

Thai

Prof. Dittaya Wanvarie

RESEARCH HIGHLIGHTS

ESG Data Analysis

In-depth analysis of corporate ESG report compliance

AI Automated Detection

Using machine learning technology for automated detection

International Cooperation

Joint research and development with multinational teams

NTCIR Certification

International top-tier information retrieval evaluation conference

Interested in participating in international collaborative research projects?

Welcome to join the ML-ESG CR 2026 research team

Visit NLPFin Official Website