GenericsKB：一个通用语句知识库
GenericsKB: A Knowledge Base of Generic Statements
摘要：
我们为NLP社区提供了一个新的资源，即一个大型（350万+句子）的 * 通用语句 * 知识库，例如，“树木从大气中去除二氧化碳”，收集自多个语料库。这是第一个包含 * 自然发生的 * 通用句子的大型资源，而不是提取或众包的三元组，因此富含高质量，通用，语义完整的语句。所有GenericsKB句子都注释了它们的主题术语，周围的上下文（句子）和（学习的）置信度。我们还发布了GenericsKB-Best（1 M+句子），包含GenericsKB中最好的泛型，并从WordNet和ConceptNet中选择合成泛型。在对两个需要多跳推理的现有数据集（OBQA和QASC）的测试中，我们发现使用GenericsKB可以比使用更大的语料库获得更高的分数和更好的解释。这表明，泛型知识库可以成为一个有用的资源，自然语言处理应用程序，以及提供数据的语言学研究的泛型及其语义。GenericsKB可从https://allenai.org/data/genericskb获得。
英文摘要：
We present a new resource for the NLP community, namely a large (3.5M+ sentence) knowledge base of *generic statements*, e.g., "Trees remove carbon dioxide from the atmosphere", collected from multiple corpora. This is the first large resource to contain *naturally occurring* generic sentences, as opposed to extracted or crowdsourced triples, and thus is rich in high-quality, general, semantically complete statements. All GenericsKB sentences are annotated with their topical term, surrounding context (sentences), and a (learned) confidence. We also release GenericsKB-Best (1M+ sentences), containing the best-quality generics in GenericsKB augmented with selected, synthesized generics from WordNet and ConceptNet. In tests on two existing datasets requiring multihop reasoning (OBQA and QASC), we find using GenericsKB can result in higher scores and better explanations than using a much larger corpus. This demonstrates that GenericsKB can be a useful resource for NLP applications, as well as providing data for linguistic studies of generics and their semantics. GenericsKB is available at https://allenai.org/data/genericskb.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
