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Related Questions
- What are the primary challenges in combining active learning with other NLP techniques for named entity recognition?
- How does the selection of relevant instances for active learning impact the overall performance of NER systems?
- What are the trade-offs between using active learning and other NLP techniques, such as transfer learning or ensemble methods, for NER tasks?
- How can active learning be effectively integrated with other NLP techniques, such as dependency parsing or semantic role labeling, to improve NER performance?
- What are the key considerations for selecting the most appropriate active learning strategy for NER tasks, given the diversity of available techniques?
- How does the choice of active learning algorithm impact the performance of NER systems, particularly in terms of accuracy and efficiency?
- What are the potential applications of active learning in NER tasks, such as text classification or sentiment analysis, and how can they be effectively integrated with other NLP techniques?
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