论文标题
NYTWIT：《纽约时报》中新颖单词的数据集
NYTWIT: A Dataset of Novel Words in the New York Times
论文作者
论文摘要
我们介绍了《纽约时报》的Word Innovation类型数据集（NYTWIT），该数据集在2017年11月至2019年3月之间在《纽约时报》上发表的2500多个新颖的英语单词集合，并为其新颖性提供了注释（例如词汇衍生，辩证，辩证法变化，混合或复合）。我们为新颖性类别的不受欢迎和上下文预测提供了基线结果，这表明即使是最先进的NLP系统也有改进的余地。我们希望这种资源通过提供新颖的单词外观的真实环境，对语言学家和NLP从业人员有用。
We present the New York Times Word Innovation Types dataset, or NYTWIT, a collection of over 2,500 novel English words published in the New York Times between November 2017 and March 2019, manually annotated for their class of novelty (such as lexical derivation, dialectal variation, blending, or compounding). We present baseline results for both uncontextual and contextual prediction of novelty class, showing that there is room for improvement even for state-of-the-art NLP systems. We hope this resource will prove useful for linguists and NLP practitioners by providing a real-world environment of novel word appearance.
