Tagging Algorithm and POS Tags for Narrator's Name in Hadith Document
Nursyahidah Alias, Nurazzah Abd Rahman, Muhammad Nazir Alias, Zulhimi Mohamed Nor, Nahdatul Akma Ahmad, Normaly Kamal Ismail · 2023
Named Entity Recognition (NER) is important in many domains, such as information retrieval and text classification. Typically, NER uses machine learning (ML) or rule-based methods to recognize NER. ML works well with annotated corpora. The most commonly used annotated corpora are in English but not in Malay. Non-annotated corpora need to be tagged to be used in NER, and manual tagging requires time and effort from experts. In this work, we proposed a Natural Language Processing (NLP) technique to automate the tagging of narrators in hadith texts. Our proposed technique includes a model for tagging narrators in hadith texts. This research used POS tags to explain the detection of narrators' names in hadith texts. A total of 700 hadith texts were used to develop the tagging model using a rule-based technique. 300 hadith documents were examined to evaluate the tagging model and resulted in 93.64% for recall and 96.72% for precision. Further research is needed to investigate the automatic extraction of the narrators' names, which can be used in hadith retrieval.