The Role of NLP in Coreference Resolution in Sindhi Text


  • Saira Baby Farooqui Shah Abdul Latif University, Khairpur, Sindh, Pakistan
  • Noor Ahmed Shaikh Shah Abdul Latif University, Khairpur, Sindh, Pakistan
  • Samina Rajper Shah Abdul Latif University, Khairpur, Sindh, Pakistan


Natural language prodessing, coreference, inflected language, machine translation


Finding terms in a text that relates to the same thing is a significant difficulty in natural language processing (NLP). We call this procedure "coreference resolution." This task is crucial for many NLP applications, such as information extraction, text summarization, and machine translation. Even though coreference resolution has been thoroughly explored in English and other commonly used languages, the difficulties presented by the Arabic language call for unique strategies catered to its unique linguistic and grammatical traits. Sindhi is a highly inflected language with a rich derivational and inflectional morphology system, flexible word order, and intricate agreement patterns. These linguistic features introduce complexities that impact traditional coreference resolution techniques. Additionally, Arabic exhibits variations across dialects, further complicating the task due to differences in syntactic structures and lexical choices.


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