How does Greek Named Entity Recognition work?
- Rule-Based Systems. Rule-based systems utilize predefined grammatical patterns to identify named entities. This method relies on manually crafted rules that define how entities should be recognized.
- Statistical Models. Statistical models are trained on annotated datasets to learn patterns in language and context, allowing them to predict labels for named entities in unseen text.
- Machine Learning. Machine learning methods involve algorithms that improve over time through experience, using a combination of supervised and unsupervised learning to enhance entity recognition accuracy.
- Deep Learning. Deep learning employs neural networks to automatically learn features from large volumes of text data, offering cutting-edge performance in named entity recognition tasks.