论文标题
使用潜在的模型调查跨语言形容词订购趋势
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
论文作者
论文摘要
跨语言，多个连续的形容词修改名词（例如“大红狗”）遵循某些未标记的订购规则。尽管已经提出了解释性帐户，但在这一领域所做的许多工作主要取决于母语者的直观判断，而不是语料库数据。我们介绍了第一个纯粹由语料库驱动的多语言形容词订购模型，即使培训和测试语言不同，该模型的形式也可以准确地跨24种不同的语言订购形容词。我们利用这种新颖的统计模型为存在通用，跨语言，分层的排序趋势的存在提供了有力的融合证据。
Across languages, multiple consecutive adjectives modifying a noun (e.g. "the big red dog") follow certain unmarked ordering rules. While explanatory accounts have been put forward, much of the work done in this area has relied primarily on the intuitive judgment of native speakers, rather than on corpus data. We present the first purely corpus-driven model of multi-lingual adjective ordering in the form of a latent-variable model that can accurately order adjectives across 24 different languages, even when the training and testing languages are different. We utilize this novel statistical model to provide strong converging evidence for the existence of universal, cross-linguistic, hierarchical adjective ordering tendencies.
