We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…

The report is the first systematic evaluation of the sentence equivalence item type introduced by the "GRE"® revised General Test. We adopt a validity framework to guide our investigation based on Kane's approach to validation whereby a hierarchy of inferences that should be documented to support score meaning and interpretation is…

In the domain of discourse processing, it has been claimed that older adults (60-0-year-olds) are less likely to encode and remember some kinds of information from texts than young adults. The experiment described here shows that they do make a particular kind of inference to the same extent that college-age adults do. The inferences examined were…

Inferences are important because not everything in the text is explicit. Therefore, the reader must generate inferences that fill in "missing" information. Various factors can influence inference processes, including those that are related to the text and reader. Moreover, these two factors are likely to interact in highly complex ways,…

This paper provides an explanation for the nonspecificity of emotion inferences found in previous research [e.g., Language and Cognitive Processes, 19(5), 613-638, 2004]. We first demonstrate that behavioral components of emotions, as opposed to emotions per se, are better markers of readers' mental representations of the main character's…

When Tarzan asks Jane "Do you like my friends?" and Jane answers "Some of them," her underinformative reply implicates "Not all of them." This "scalar inference" arises when a less-than-maximally informative utterance implies the denial of a more informative proposition. Default Inference accounts (e.g.,…