论文标题
伯特知道蓬塔卡纳不仅美丽，而且很漂亮：排名标量形容词，具有上下文的表示形式
BERT Knows Punta Cana is not just beautiful, it's gorgeous: Ranking Scalar Adjectives with Contextualised Representations
论文作者
论文摘要
诸如漂亮，美丽和华丽的形容词描述了他们修改但强度不同的名词的正面特性。这些差异对于自然语言理解和推理很重要。我们提出了一种基于BERT的新型方法来检测标量形容词。我们通过直接从上下文化表示形式得出的向量对强度进行建模，并表明它们可以成功对标量形容词进行排名。我们在本质上，金标准数据集以及间接答案任务上评估了我们的模型。我们的结果表明，Bert编码有关标量形容词语义的丰富知识，并且能够比静态嵌入式和以前的模型提供更好的质量强度排名。
Adjectives like pretty, beautiful and gorgeous describe positive properties of the nouns they modify but with different intensity. These differences are important for natural language understanding and reasoning. We propose a novel BERT-based approach to intensity detection for scalar adjectives. We model intensity by vectors directly derived from contextualised representations and show they can successfully rank scalar adjectives. We evaluate our models both intrinsically, on gold standard datasets, and on an Indirect Question Answering task. Our results demonstrate that BERT encodes rich knowledge about the semantics of scalar adjectives, and is able to provide better quality intensity rankings than static embeddings and previous models with access to dedicated resources.
