Collaborative Research: Construction and Utility of a Large Scale Semantic Priming Database

人类语言在本质上是完全语境化的。这一事实可以通过考虑一个声音、单词、句子或段落的含义如何在脱离上下文或置于不同的上下文时发生急剧变化而清楚地看到。语言的语境本质已经被证明是开发能够理解或产生语言的计算机算法的主要挑战，然而人类在语境中处理语言如此容易，以至于我们通常甚至没有意识到它。语言和认知科学家几十年来一直在研究人类如何处理语境，通常是关于其他单词的语境中的单个单词。例如，人们公认的是，当一个人识别像“狗”这样的单词的能力在像“猫”这样的单词之后不久出现时会得到增强，这在意义上是相关的。像这样的结果被称为“语义启动”，我们对语义启动和其他类型的语境效应背后的机制的了解主要是基于使用少量词汇进行的研究，这些词汇被选择来提出非常有针对性的理论观点。在国家科学基金会的支持下，Hutchison和Balota博士将采取互补的方法来研究语义启动的机制。研究人员将为超过3,000个英语单词的语义启动结果开发一个大型数据库，而不是将其范围限制在一小撮单词上。该数据库将包括一系列关于词汇及其用法的统计数据，这些数据将通过一个功能强大的网络界面提供给研究界。该数据库将帮助世界各地的研究人员推进这一过程的理论和计算模型，使人类不仅能够克服语境的挑战，而且能够实际利用语境来理解和产生语言。

Human languages are thoroughly contextual in nature. This fact can be seen plainly by considering how the meaning of a sound, word, sentence, or passage can change drastically when taken out of context, or placed in a different context. The contextual nature of language has proven to be a major challenge for developing computer algorithms that can understand or produce language, yet humans process language in context so easily that we are usually not even aware of it. Linguistic and cognitive scientists have been studying how humans process context for decades, often with respect to individual words in the context of other words. For instance, it is well established that a person's ability to recognize a word like "dog" is enhanced when it appears shortly after a word like "cat" that is related in meaning. Results like these are referred to as "semantic priming", and our knowledge of the mechanisms that underlie semantic priming and other kinds of contextual effects is mostly based on research using small handfuls of words chosen to make very targeted theoretical points. With support of the National Science Foundation, Drs. Hutchison and Balota will take a complementary approach to studying the mechanisms of semantic priming. Rather than restricting their scope to small handfuls of words, the investigators will develop a large database of semantic priming results for over 3,000 words of English. The database will include a range of statistics about the words and their usages, and the data will be made available to the research community via a powerful web interface. The database will help researchers throughout the world to advance theories and computational models of the processes that allow humans to not only overcome the challenge of context, but actually use context to their advantage in the comprehension and production of language.