In this article, you use their term and named entity extraction services to perform text analysis.
在本文中，您使用他们的术语和指定实体抽取服务来执行文本分析。
Text of these entity types are marked with a light blue rectangle on the screen.
屏幕上这些实体类型的文本已经用亮蓝色矩形屏蔽。
You can use built-in text analysis functions, namely dictionary based and regular expression based named entity extraction, as explained in the previous articles of this series.
您可以使用内置的文本分析特性，即基于词典和基于正则表达式的命名实体提取，如本系列的前面的文章所述。
An attacker could also exponentially build up entity references purely in the internal DTD subset so that a small input document produces a large quantity of text.
攻击者也可以根据指数只在内部dtd子集中有规律地建立实体引用，这样，就会使小的输入文档制造出大量的文本。
All fields of an entity can be indexed as if it was a single document, and then regular text searches can be performed to retrieve the matching entities.
所有实体的字段可以像只有一个文件那样被索引，并且是正则文本搜索可以匹配的实体。
Entities are references to data; depending on the kind of entity, the XML parser will either replace the entity reference with the entity's replacement text or the contents of an external document.
实体是对数据的引用；根据实体种类的不同，xml解析器将使用实体的替代文本或者外部文档的内容来替代实体引用。
Named entities can act like macros, letting you replace repetitive or difficult text with entity references.
命名实体的作用类似于宏，允许您使用实体引用替代重复或难以输入的文本。
So we consider a text as a structured entity, or perhaps as an entity which is structured and yet at the same time that's the case with Roland Barthes.
所以，我们把原文视为一个结构上的实体，或者是作为一个，有结构上的实体同时，这就是罗兰，巴特的例子。
This code identifies the text that stands in for the entity.
这个代码识别表示实体的文本。
When declaring a named entity, you specify the entity's name, and its replacement text.
在声明命名实体时，指定实体的名称及其替代文本。
All text and character entities MUST be converted to string (e.g., STR_I) or entity (entity) tokens.
所有的文本和字符实体都必须转换成字符串(如str_i)或实体(ENTITY)标记。
Although the token "IBM" is the direct text Node of element "entity," and the scope for the text search is XML element "sentence," the query returns a hit.
尽管符号“IBM”是元素“entity”的直接文本节点，而文本搜索的范围是XML元素“sentence”，但是查询找到了一个结果。
For instance, a String attribute of an entity could be implemented as a CHAR, VARCHAR, or TEXT type of column.
例如，可以将实体的String类型的属性实现为CHAR、VARCHAR或text类型的列。
To use a symbol in your text, you must set it up as an entity using its character code.
如果要在文本中使用符号，必须使用它的字符代码将它设置为实体。
Algorithms that scan text for common patterns, such as email addresses, phone Numbers, and people and place names, are useful for named entity extraction.
为总结公共模式(比如，电子邮箱地址、电话号码、人名和地名)而扫描文本的算法对于指定实体抽象非常有用。
It can also make it easier to adjust the text-perhaps if the company name changes-in many places with a simple adjustment in the entity definition.
在很多情况下它还使得调整文本更加容易(变更公司名时)，只需对实体定义进行简单调整。
The parameter entity replacement text must nest properly within markup declarations.
参数实体替换文本必须正确嵌套在标记声明中。
Only one passage of Front-Cover Text and one of Back-Cover Text may be added by (or through arrangements made by) any one entity.
前封面文字和后封面文字都只能有一个段落，可以经由任何一个实体，或经由任何一个实体所作出的安排而被加入。
Some people do not want the text and prefer to use an extended character or HTML character entity to move the reader on to the full post.
有的人不想要文章，更喜欢使用一个延伸的字符，或者HTML字符实体来引导读者阅读整篇文章。
Named entity recognition is the first key stage of text mining in the exploding biomedical literature.
命名实体识别是生物医学文献文本挖掘重要的第一步。
If there is no entity declaration that matches, an empty text node is attached as the only child of the entity reference node.
如果没有匹配的实体声明，则附加一个空的文本节点作为实体引用节点的唯一子级。
In this way de Man can read the text as rigorously as possible in terms of what the text itself—as a rhetorical entity—makes possible, even necessary.
用这种方法，德曼可以进行一种残酷的阅读，发现文本可提供的一切可能性。
Find and Replace window to search for text strings, expressions, or entity names within the code of your documents.
“查找替换”窗口可用于在文档的代码中搜索文本字符串、表达式或实体名称。
If the Document already includes a cover text for the same cover, previously added by you or by arrangement made by the same entity you are acting on behalf of, you may not add another;
如果文件已经在同样的封面包括了封面文字--先前由你或由你所代表的相同实体所作出的安排而加入，则你不可以增加另外一个；
But majority of them are based on statistic computation, lack feedback system mechanism, and ignore that the whole text is an organic entity.
但是这些算法大部分都是基于统计计算的，缺乏反馈体系机制，忽略了文本整体的有机性和文本之间的联系性。
In this paper, the maximum entropy principle is used to extract Chinese entity from free text.
采用最大熵原理实现汉语实体提取。
Any markup, such as syntax to be recognized as an entity reference, is treated as literal text and needs to be properly escaped by the implementation when it is written out.
任何标记(例如将被识别为实体引用的语法)都被当做文本对待，当将其写出时，需要由实现对其进行正确地转义。
Town in this text was a business entity which located between the county city and small village and had some independence in the Ming and Qing period.
本文所言之市镇，是指明清时期介于县城与村落之间的具有相对独立性的商业实体。
Town in this text was a business entity which located between the county city and small village and had some independence in the Ming and Qing period.
本文所言之市镇，是指明清时期介于县城与村落之间的具有相对独立性的商业实体。
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