On the use of Silver Standard Data for Zero-shot Classification Tasks in Information Extraction

arXiv:2402.18061v1 Announce Type: new
Abstract: The superior performance of supervised classification methods in the information extraction (IE) area heavily relies on a large amount of gold standard data. Recent zero-shot classification methods converted the task to other NLP tasks (e.g., textual entailment) and used off-the-shelf models of these NLP tasks to directly perform inference on the test data without using a large amount of IE annotation data. A potentially valuable by-product of these methods is the large-scale silver standard data, …

arxiv classification cs.ai cs.cl data extraction information information extraction standard tasks type zero-shot