How does Yiddish Named Entity Recognition work?
- Rule-Based Systems. This method uses predefined rules and dictionaries to identify named entities based on linguistic patterns and context within the Yiddish language.
- Machine Learning. Machine learning approaches train models on annotated Yiddish datasets to recognize named entities through pattern recognition and statistical analysis.
- Deep Learning. Utilizing neural networks, deep learning techniques can automatically learn to identify named entities by processing large amounts of Yiddish text with high accuracy.
- Hybrid Approaches. Hybrid systems combine rule-based and machine learning methods to enhance the performance of Yiddish NER by leveraging the strengths of both techniques.
