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 1,562 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.
@article{arxiv.2205.07712,
title = {Persian Abstract Meaning Representation: Annotation Guidelines and Gold Standard Dataset},
author = {Reza Takhshid and Tara Azin and Razieh Shojaei and Mohammad Bahrani},
journal= {arXiv preprint arXiv:2205.07712},
year = {2025}
}