文本推理在自然语言处理的应用中占有极为重要的位置，本文介绍了基于知网的一种推理方法，该方法以语义网络的形式表示知网中的知识，利用“标记传递”实现推理。
Text inference is central to natural language applications. This paper presents an inference method based on HowNet, which organizes knowledge with semantic net and infers with marker passing.
最后，如此一系列的演绎推理将能处理整个句子和段落，从而生成一个精确的文本意义的陈述。
At the end, a series of deductions like these would handle entire sentences and paragraphs to yield an accurate text-meaning representation.
探讨文本阅读过程中目标焦点是否引起即时的预期推理。
Moving window display technique was used to investigate the predictive inference elicited by goal-focus information during text reading.
在解释程序的设计中，采用预置文本与路径跟踪法，可以在用户需要时给出推理结果和过程的详细解释。
In the design of interpretive program, employ preset text and path tagging method to get inference result and explanation of process in detail when users demand.
本研究通过三个实验考察了语义联系和因果制约对文本阅读中预期推理激活和编码的贡献。
This study mainly deals with the influence of working memory capacity on the generation of predictive inference during text reading.
研究采用动窗技术探讨了文本阅读中需要简单推理情境下的信息整合发生的时机。
This study used a moving-window method to explore the information integration process under the condition of simple inference in text-reading task.
采用预设文本法的解释机制，对系统推理结果进行输出方式的设计。
Using the interpreted mechanisms, which format the text in advance, to design the output mode of system inference results.
该理论综合了现有问答系统的优点，有望基于纯粹的文本知识，实现检索、理解、推理一体化的机制。
This theory combined the excellence of current Question Answering System and is hoped to fulfill the mechanism of retrieval, understanding and reasoning based on pure text knowledge.
在研究现有文本信息检索技术的基础上，设计了基于推理网络的文本检索模型。
By the research on the existent IR (Information retrieval) technology, a text retrieval model based on inference network is designed.
人类的交际内容不仅依赖于文本本身，还受制于交际推理中的语境。
What is conveyed in human communication is determined not only by the text, but also the inferential context.
人类的交际内容不仅依赖于文本本身，还受制于交际推理中的语境。
What is conveyed in human communication is determined not only by the text, but also the inferential context.
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