从RDF图中删除三元组。
它提供前面提到的三元组的识别和解释方法。
It's how the triples that I mentioned earlier are identified and interpreted.
然后后续处理就是操作和查询存储中的三元组。
Subsequent processing then takes the form of manipulating and querying the triples in the store.
图2：治理三元组的每个组件都供给另一个组件。
Figure 2: Each component of the governance triad feeds another component.
还应该记住，RDF 三元组的组件通常是URI。
You should also remember that the components of an RDF triple are usually URIs.
由于每个命题都有主语、谓词和宾语，也被称为三元组。
Because every statement has a subject, predicate, and object, it is also referred to as a triple.
RDF陈述是一个三元组(主题、属性、对象)。
RDF statements are made up of triples (subject, property, object).
现在，剩下的就是存储四元组，而不是存储三元组。
查询在具有WHERE子句中的所有三元组的图形中查找语句。
The query finds statements in the graph for which all of the triples in the WHERE clause hold.
在RDF处理器将这一部分解析成三元组时，我获得了清单2中显示的数据。
When this is parsed into triples by an RDF processor, I obtain the data shown in Listing 2.
随后rdf应用程序所要操作的就是清单2中显示的这列三元组了。
It is the list of triples shown in Listing 2 that is then acted on by RDF applications.
其语法类似于SQL,SPARQL查询包括一系列的三元组范型和修饰符。
Its syntax is similar to that of SQL, and SPARQL queries consist of a series of triple patterns and modifiers.
WHERE子句引入第二个变量concept并定义与图形匹配的三元组。
The WHERE clause introduces a second variable, concept, and defines triples that are matched against the graph.
合并数据(不同的图)是一项简单操作，只需要建立包含图中所有三元组的集合。
Merging data (different graphs) is a simple operation that involves constructing a set of triples that includes all of the triples from the graphs.
这些是由对象-属性-值三元组表示的——即对象o拥有属性A，属性a的值是V。
These are represented by object-attribute-value triples — that is, an object o has an attribute a with the value v.
这些样式表的输出是资源描述框架(RDF)三元组，可以用功能丰富的RDF工具集处理。
The output from these stylesheets are Resource Description Framework (RDF) triples that you can process with the underutilized RDF toolset.
您会发现Node - Arc - Node关系(三元组)比关系数据库模型更易于理解。
You may find Node-Arc-Node relationships (triple) easier to understand than relational database models.
当参考下列两个RDF图表时我们可以看到，第一个是由一个单独的三元组形成的。
This may be illustrated by considering the following two RDF graphs, the first of which consists of a single triple.
处理RDF然后存储它的应用程序使用三元组存储(triple store)来做到这一点。
Applications that process RDF and then store it use triple stores to do this.
小心：我曾看到过许多N -Triples示例中的注释位于三元组所在行的结束小数点之后。
Be careful: I have seen many N-Triples examples with comments on the same line as a triple, after the closing period.
了解它为什么在那里很重要，其原因是about属性定义“主语-谓语-宾语”三元组中的主语。
It's important to know why it's there: the about attribute defines the subject in that subject-predicate-object triple concept I mentioned previously.
在RDF 中，这个三元组将根据一种特殊格式编码，这种格式用于识别卡通人物和他们的主要敌人。
In RDF, this triple would be encoded based on the format used to identify cartoon characters and their arch-enemies.
客户机向流程管理器发送了一条带有适当的三元组的消息之后，就会有一个流程实例被创建并开始运行。
Once a client sends a message to a process manager with the appropriate triplet, a process instance is created and starts running.
图形模式的第二个三元组与contributor的foaf：weblog属性对应的对象匹配。
The graph pattern's second triple matches the object of the contributor's foaf: weblog property.
有开源和商业工具可用于将这些格式的数据转换成三元组，从而让您可以轻松组合多个来源、不同格式的数据。
Open source and commercial tools are available to convert data in these formats to triples, giving you an easy way to combine data from multiple sources using different formats.
由于将数据直接分解成三元组，所以XML工具(象xpath或XQuery)就没有多少用处了。
As the data is directly decomposed into triples, XML tools like XPath or XQuery aren't a lot of use.
开源的D2RQ接口让您可以将关系数据当作一个三元组集合对待，因而该数据可以合并到这样的应用程序中。
The open source D2RQ interface lets you treat relational data as a collection of triples so that this data can be incorporated into such an application.
例如，如果一个关系数据库或电子表格说雇员94321的雇佣日期是2007-10-14，那么很容易表达为三元组。
For example, if a relational database or spreadsheet says that employee 94321 has a hire-date value of 2007-10-14, it would be easy to express this as a triple.
例如，如果一个关系数据库或电子表格说雇员94321的雇佣日期是2007-10-14，那么很容易表达为三元组。
For example, if a relational database or spreadsheet says that employee 94321 has a hire-date value of 2007-10-14, it would be easy to express this as a triple.
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