Reza Takhshid


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2024

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Persian Abstract Meaning Representation: Annotation Guidelines and Gold Standard Dataset
Reza Takhshid | Tara Azin | Razieh Shojaei | Mohammad Bahrani
Proceedings of the 2024 UMR Parsing Workshop

This paper introduces the Persian Abstract Meaning Representation (AMR) guidelines, a detailed guide for annotating Persian sentences with AMR, focusing on the necessary adaptations to fit Persian’s unique syntactic structures. We discuss the development process of a Persian AMR gold standard dataset consisting of 1562 sentences created following the guidelines. By examining the language specifications and nuances that distinguish AMR annotations of a low-resource language like Persian, we shed light on the challenges and limitations of developing a universal meaning representation framework. The guidelines and the dataset introduced in this study highlight such challenges, aiming to advance the field.