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A generative-informed neuro-symbolic framework for syntactic ambiguity resolution: Evidence from Arabic DPs

arXiv · · Significant research

NLP Arabic AI Research LLM

Summary

A new generative-informed neuro-symbolic framework has been proposed to resolve syntactic ambiguity in Modern Standard Arabic (MSA) DPs. This framework integrates generative syntactic notions with AraBERT, treating ambiguity as a candidate-based decision task evaluated through candidate-conditioned input representations. The model achieved high performance, including 96.88% accuracy and 95.92% macro-F1 on an unseen evaluation set. Why it matters: This study offers a controlled and interpretable approach to Arabic syntactic ambiguity resolution, demonstrating an effective method for integrating formal linguistic representations with contextual neural modeling in Arabic NLP.

Keywords

Syntactic ambiguity · Arabic NLP · Neuro-symbolic framework · AraBERT · Generative syntax

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