122 research outputs found
A Survey on Recent Named Entity Recognition and Relation Classification Methods with Focus on Few-Shot Learning Approaches
Named entity recognition and relation classification are key stages for
extracting information from unstructured text. Several natural language
processing applications utilize the two tasks, such as information retrieval,
knowledge graph construction and completion, question answering and other
domain-specific applications, such as biomedical data mining. We present a
survey of recent approaches in the two tasks with focus on few-shot learning
approaches. Our work compares the main approaches followed in the two
paradigms. Additionally, we report the latest metric scores in the two tasks
with a structured analysis that considers the results in the few-shot learning
scope
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