Deep Named Entity Recognition in Hindi Using Neural Networks

In Natural Language Processing, named entity recognition (NER) is a task of (NLP) that tries to automatically identify and annotate Named Entities in text, such as people, places, organisations. We employ deep learning-based architecture this work solve the problem recognising entities Hindi text phrase. literature, approaches based on bidirectional long short-term memory (BiLSTM) have been utilized for NER task. performed recursive BiLSTM study, which includes de-noising autoencoder with conditioning logic. Experiments were undertaken examine behaviour individual word embeddings batch sizes, vital training models. The findings suggested system architecture, well comparison performance characteristics existing systems, are presented study.