论文标题
英雄，恶棍和受害者以及GPT-3：在没有培训数据的情况下自动提取角色角色
Heroes, Villains, and Victims, and GPT-3: Automated Extraction of Character Roles Without Training Data
论文作者
论文摘要
本文展示了如何使用大规模的预训练的语言模型从叙事文本中提取角色角色，而无需培训数据。 GPT-3通过零射击提示提示询问，可以在不同领域中识别英雄，反派和受害者：报纸文章，电影情节摘要和政治演讲。
This paper shows how to use large-scale pre-trained language models to extract character roles from narrative texts without training data. Queried with a zero-shot question-answering prompt, GPT-3 can identify the hero, villain, and victim in diverse domains: newspaper articles, movie plot summaries, and political speeches.
