教会学生歧义消除的方法对于提高其听、说、读、写、译能力有重要意义。
Helping students to adopt strategies of disambiguation is very important to improve their abilities of listening, speaking, reading, writing and translating.
字典的第二部份由13060个汉字及它们的使用频率组成（Tsai,1996b），汉字的频率在最后一个歧义消除规则之中使用。
The second part of the lexicon consisted of 13,060 characters and their frequency of usage (Tsai, 1996b). Character frequency was used in the last ambiguity resolution rule.
每个元素前面都有一个名称空间标签，以消除元素表示的内容的所有歧义。
Each of the elements is preceded by a namespace label that removes all ambiguity as to what the element represents.
要消除歧义，最明显的方法就是提供一个直接明了的句子，该句子包含其他一些特定细节来说明上下文。
The most obvious way to remove doubt is to provide an up-front, explicit statement including additional specific details to make the context clear.
然而，可能不必对整个文本消除歧义：一个完全具有代表性的摘要就足够了。
However, it might not be necessary to disambiguate an entire text: a thoroughly representative abstract might be sufficient.
请注意，策略中的第一个图标是消除歧义的“匹配”操作，此操作是设备在规则之间做出决定所必需的。
Notice that the very first icon in the policy is a disambiguation "match" action that is required by the device to decide between multiple rules.
注意，在这里，为展示基本要点，我选择只消除名词和动词的歧义。
Note that, at this point, I chose to disambiguate the nouns and the verb only to make a basic point.
RDF并不严格要求特性名的名称空间，但极力建议将它作为消除这些名称的歧义的方法。
Namespaces on property names are not strictly required for RDF, but are highly recommended as a way to disambiguate such names.
下面的例子消除了组合两个文档时对某一公共元素产生歧义。
This is an example of disambiguating a common element when two documents are combined.
您可能会说，“消除文本歧义所花的时间可能会是作者撰写文本的时间的10倍！”
Disambiguating any text would likely take a writer 10 times as long as writing the text!
除了最大匹配算法，许多其它消除歧义的算法也已经被得出。
Besides maximum matching, many other disambiguation algorithms have been proposed. Various information are used in the disambiguation process.
术语表不需要列出需求规格说明书中用过的每一个词汇，但是它必须包含可能有歧义的词汇。 术语表通过给出需求规格说明书中关键词汇的定义，消除了模糊性。
The glossary does not need to list every term used in the requirement specifications, but it should definitely include any that might be subject to multiple interpretations.
我们的心理通过在无意义中消除歧义获得意义。
在其官方博客上，有这么一篇文章提到说恰当的总结提炼对消除文章的模糊与歧义是如何之好。
There is a great article over at their blog about how great summaries disambiguate topics.
要获取一个使用这种类型的消除歧义技术的简单搜索引擎示例，请参见DAMSEL(参见参考资料获取链接)。
For an example of a simple search engine that USES this type of disambiguation, see DAMSEL (see Resources for the link).
这样，创建XPath的任何人必须准备创建新的前缀来消除这些冲突所带来的歧义，并确保那些前缀不与正在使用中的任何其它前缀发生冲突。
So anyone creating an XPath has to be prepared to create new prefixes to disambiguate these collisions, and make sure those prefixes don't collide with any others already in use.
您可能已经猜到，这个添加消除了经典Groovy中的歧义性。
This addition, as you've probably guessed, clears up ambiguities in classic Groovy.
因为XMLNamespaces 1.0不允许应用程序将缺省名称空间用作属性，所以我们必须明确地指定前缀来消除歧义。
Since XML Namespaces 1.0 does not allow application of the default namespace to attributes, we must explicitly specify the prefix to disambiguate.
输出n 02 403454v01963942 n09358358告知机器消除了歧义的内容。
The output, n02403454 v01963942 n09358358, informs the machine of the disambiguated content.
对于文本，消除歧义很重要，原因有几个，可能包括。
With respect to text, disambiguation is important for a number of reasons. A few reasons might be.
您可能会以蓝色显示cow、jumped和moon，并在读者将鼠标悬停于这些单词上方时在一个弹出窗口中提供WordNet信息(就像我此前在“消除歧义的基本方法”部分所做的那样)。
You might display cow, jumped, and moon in blue and provide the WordNet information in a pop-up when the reader hovers over the word (as I did earlier in the section "Basic disambiguation").
本文将着重从语用学的角度，探讨语境如何通过制约和解释功能来消除和识别语用歧义。
This paper argues on how to eliminate and distinguish pragmatic ambiguity by taking advantage of the restrictive and interpretive function of context.
根据歧义的来源将歧义句分为“的”字结构歧义、移位造成的歧义和逻辑歧义三类，并提出采取不同的手段消除歧义。
This article discusses possible means for eliminating the syntactical ambiguity from three aspects: the ambiguity of the structure of "DE", that of shifting in deep structure and that of logic form.
这部分主要是通过分析维特根斯坦关于理解、思考、知道、解释的日常语言记录来消除人们在日常生活中运用这些词语的歧义。
This section mainly analyzes the recordings of Wittgenstein's daily language about understanding, thinking, knowing in order to eliminate ambiguity when people using these words in everyday life.
本文从语音、词汇、语法三个方面对英语歧义现象进行了探讨，分析了英语歧义现象产生的原因，提出了消除英语歧义的一些基本方法。
The article probes into the English ambiguity from the aspects of the phonetics, the lexicology, as well as the grammar, analyzes the cause of it, and also puts forward some basic ways to remove it.
从实验结果中看出，该模型能有效提高安全审计系统的识别精度，消除分片语义歧义性。
The experiments show that the fragment audit model could improve the discernment precision of security audit systems efficiently and eliminate the fragment semantic ambiguity.
概念间关系是本体的重要组成部分，概念间关系的细化可以消除概念的歧义性。
Concept-concept relationship is an important component of ontology. The elaboration of the concept-concept relationship can resolve the ambiguity of the concept.
引入scnf语法，据此进行概率CYK剖析，得到句子的最佳剖析树以消除歧义。
Stochastic Chomsky normal form (SCNF) is introduced to parse sentences with probabilistic CYK algorithm. The optimal parsing trees of sentences are gained to eliminate ambiguous meanings.
本文论述了跨语言信息检索中翻译歧义性问题产生的原因，并且总结了目前消除这种歧义的方法和技术。
This paper discusses the cause of translation ambiguity in CLIR, and summarizes the methods and techniques of translation disambiguation at present.
本文论述了跨语言信息检索中翻译歧义性问题产生的原因，并且总结了目前消除这种歧义的方法和技术。
This paper discusses the cause of translation ambiguity in CLIR, and summarizes the methods and techniques of translation disambiguation at present.
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