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Speech perception involves prediction, but how is that prediction implemented? In cognitive models prediction has often been taken to imply that there is feedback of activation from lexical to pre-lex...
We present a system for textual inference (the task of inferring whether a sentence follows from another text) that uses learning and a logical-formula semantic representation of the text. More precis...
We present a system for deciding whether a given sentence can be inferred from text. Each sentence is represented as a directed graph (extracted from a dependency parser) in which the nodes represent ...
This paper presents our work on textual inference and situates it within the context of the larger goals of machine reading. The textual inference task is to determine if the meaning of one text can b...
This paper presents the first use of a computational model of natural logic—a system of logical inference which operates over natural language—for textual inference. Most current approaches to the PAS...
We propose an approach to natural language inference based on a model of natural logic, which identifies valid inferences by their lexical and syntactic features, without full semantic interpretation....
We propose a model of natural language inference which identifies valid inferences by their lexical and syntactic features, without full semantic interpretation. We extend past work in natural logic, ...
There is little consensus regarding the circumstances in which people spontaneously generate causal inferences, and in particular whether they generate inferences about the causal antecedents or the c...
Greed is Good if Randomized: New Inference for Dependency Parsing。
One of the most common findings of recent reading research is that drawing inferences is an essential part of the comprehension process, even among young children (Anderson & Pearson, 1984). Dole et a...
Delimiting the Theme of the English Clause - An Inference-boundary Account。

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