Update README.md

README.md

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 We develop standardized frameworks and tools for analyzing privacy policies, enabling researchers and practitioners to:
 
 - Identify dark patterns and deceptive practices in privacy disclosures
-- - Compare privacy practices across companies and sectors
-  - - Build machine learning models for automated policy analysis
-    - - Track regulatory compliance across jurisdictions
-     
-      - ## Projects
-     
-    - ### OPPT v1.0 Taxonomy
-    - A comprehensive 14-category taxonomy for privacy policy classification, extending the foundational OPP-115 scheme with modern regulatory categories (GDPR, CCPA/CPRA, AI Act).
-  - ### OPPT-2026 Dataset
-  - 123 privacy policies from major technology companies annotated using OPPT v1.0, featuring:
-  - - 3,600+ annotated segments
-    - - Two-agent LLM consensus methodology
-      - - Rich attribute schemas
-        - - Modern regulatory landscape (January 2026)
-         
-          - ## Research Areas
-         
-        - - Privacy policy analysis and NLP
-          - - Dark pattern detection
-            - - Regulatory compliance automation
-              - - Consumer privacy protection
-               
-                - ## Contact
-               
-              - - **Inquiries**: tebrackin@outlook.com
-                - - **Commercial licensing**: tebrackin@outlook.com
-                 
-                  - ---
-
-                  *Building tools for a more transparent digital privacy landscape*
+- Compare privacy practices across companies and sectors
+- Build machine learning models for automated policy analysis
+- Track regulatory compliance across jurisdictions
+
+## Projects
+
+### OPPT v1.0 Taxonomy
+
+A comprehensive 14-category taxonomy for privacy policy classification, extending the foundational OPP-115 scheme with modern regulatory categories (GDPR, CCPA/CPRA, AI Act).
+
+### OPPT-2026 Dataset
+
+123 privacy policies from major technology companies annotated using OPPT v1.0, featuring:
+
+- 3,600+ annotated segments
+- Two-agent LLM consensus methodology
+- Rich attribute schemas
+- Modern regulatory landscape (January 2026)
+
+## Research Areas
+
+- Privacy policy analysis and NLP
+- Dark pattern detection
+- Regulatory compliance automation
+- Consumer privacy protection
+
+## Contact
+
+- **Inquiries**: tebrackin@outlook.com
+- **Commercial licensing**: tebrackin@outlook.com
+
+---
+
+*Building tools for a more transparent digital privacy landscape*