<p>Anaphora resolution, a process for identifying the antecedents for an anaphoric expression, is critical to numerous Natural Language Processing (NLP) tasks, including question-answering systems, machine translation, and summarization systems. The development and evaluation of such NLP models necessitate annotated corpora. Although substantial efforts have been made to develop linguistic resources, there remains a notable deficiency in low-resource languages, including Punjabi. To bridge this gap, a Punjabi anaphoric annotation tool has been developed to tackle the challenges posed by repetitive tasks inherent in manual annotation processes and significantly streamline the creation of an annotated anaphoric corpus. The tool enables annotators to concentrate on complex and intricate details. The developed tool has been employed to create a Punjabi anaphoric annotated corpus, achieving an inter-annotator agreement of 81% marking a significant advancement in Punjabi computational linguistics. The tool integrates various pre-processing phases such as tokenization, POS tagging, pruning, chunking, and head computation into a single web-based interface. Additionally, it provides modules that facilitate the incorporation of features. The web-interface makes it remotely accessible for the annotator. The tool and corpus enhance anaphora resolution capabilities and lay the ground for further research in other low-resource languages. The effectiveness of the tool and corpus in addressing anaphora and associated challenges within the domain of Punjabi computational linguistics is significant. This manuscript focus on the development of anaphoric annotation tool and creation of a corpus using the tool, for the Anaphora Resolution System (ARS).</p>