Sentence Segmentation

Sentence segmentation, the task of dividing text into individual sentences, is a fundamental preprocessing step in many natural language processing (NLP) applications. Current research focuses on developing robust and efficient methods that handle diverse text formats, including poorly punctuated or multilingual documents, often employing techniques like rule-based systems, statistical models, and increasingly, large language models (LLMs) for improved accuracy and adaptability across domains. These advancements are crucial for improving the performance of downstream NLP tasks such as machine translation, fact extraction, and question answering, as accurate sentence segmentation directly impacts the quality of subsequent analysis. The development of high-quality, multilingual datasets and the exploration of novel model architectures, such as those incorporating prosodic features or leveraging in-context learning, are driving significant progress in this field.