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  The information covered by the Knowledge Graph grew significantly after launch, tripling its size within seven months (covering 570 million '''entities''' and 18 billion '''facts''') and answering "roughly one-third" of the 100 billion monthly searches Google processed in May 2016. The Knowledge Graph has been criticized for providing answers without source attribution or citation.

  The information covered by the Knowledge Graph grew significantly after launch, tripling its size within seven months (covering 570 million '''entities''' and 18 billion '''facts''') and answering "roughly one-third" of the 100 billion monthly searches Google processed in May 2016. The Knowledge Graph has been criticized for providing answers without source attribution or citation.

谷歌知识图谱涵盖的内容在其推行后迅速增长，7个月内增长了三倍(涵盖了5.7亿个<font color="#32cd32">实体</font>和180亿条<font color=#32cd32>信息关系</font>)，并解决了谷歌每月处理的1000亿次搜索中“大约三分之一”的问题。到2020年5月，这个数字已经增长到5000亿，涉及50亿个信息点（p.s.该句是从最新wikipedia词条上补充的）。因为知识图谱的内容没有来源或引用而引起了许多争议。

谷歌知识图谱涵盖的内容在其推行后迅速增长，7个月内增长了三倍(涵盖了5.7亿个<font color="#32cd32">实体</font>和180亿条<font color=#32cd32>信息关系</font>)，并解决了谷歌每月处理的1000亿次搜索中“大约三分之一”的问题。到2020年5月，这个数字已经增长到5000亿，涉及50亿个信息点---[[用户:Thingamabob|Thingamabob]]（[[用户讨论:Thingamabob|讨论]]）。因为知识图谱的内容没有来源或引用而引起了许多争议。

The Knowledge Graph was powered in part by [[Freebase (database)|Freebase]].<ref>{{cite web |url= http://googleblog.blogspot.com/2012/05/introducing-knowledge-graph-things-not.html |title=Introducing the Knowledge Graph: Things, Not Strings |work=Google Official Blog  

The Knowledge Graph was powered in part by [[Freebase (database)|Freebase]].<ref>{{cite web |url= http://googleblog.blogspot.com/2012/05/introducing-knowledge-graph-things-not.html |title=Introducing the Knowledge Graph: Things, Not Strings |work=Google Official Blog </ref>

The Knowledge Graph was powered in part by Freebase.<ref>{{cite web |url= http://googleblog.blogspot.com/2012/05/introducing-knowledge-graph-things-not.html |title=Introducing the Knowledge Graph: Things, Not Strings |work=Google Official Blog  

The Knowledge Graph was powered in part by Freebase.<ref>{{cite web |url= http://googleblog.blogspot.com/2012/05/introducing-knowledge-graph-things-not.html |title=Introducing the Knowledge Graph: Things, Not Strings |work=Google Official Blog</ref>

该知识图谱由<font color=#32cd32>Freebase</font>（p.s该网站名字未找到对应中文翻译)部分支持。

该知识图谱由<font color=#32cd32>Freebase</font>---[[用户:Thingamabob|Thingamabob]]（[[用户讨论:Thingamabob|讨论]]）部分支持。

In August 2014, ''[[New Scientist]]'' reported that Google had launched '''Knowledge Vault'''.<ref>{{cite web |first=Hal |last=Hodson |title=Google’s fact-checking bots build vast knowledge bank |url=https://www.newscientist.com/article/mg22329832-700-googles-fact-checking-bots-build-vast-knowledge-bank/ |website=[[New Scientist]] |date=August 20, 2014 |accessdate=December 10, 2017}}</ref> After publication, Google reached out to ''[[Search Engine Land]]'' to explain that Knowledge Vault was a research paper, not an active Google service, and in its report, ''Search Engine Land'' referenced indications by the company that "numerous models" were being experimented with to examine the possibility of automatically gathering meaning from text.<ref>{{cite web |first=Greg |last=Sterling |title=Google "Knowledge Vault" To Power Future Of Search |url=https://searchengineland.com/google-builds-next-gen-knowledge-graph-future-201640 |website=[[Search Engine Land]] |date=August 25, 2014 |accessdate=December 10, 2017}}</ref>  The Knowledge Vault was meant to deal with facts, automatically gathering and merging information from across the Internet into a knowledge base capable of answering direct questions, such as "Where was [[Madonna (entertainer)|Madonna]] born". It was reported that its main ability over the Knowledge Graph was to gather information automatically rather than relying on crowd sourced facts compiled by humans; by the time of the 2014 report, it had collected over 1.6 billion facts, 271 million of which were considered "confident facts", a term for information deemed more than 90% true.

In August 2014, ''[[New Scientist]]'' reported that Google had launched '''Knowledge Vault'''.<ref>{{cite web |first=Hal |last=Hodson |title=Google’s fact-checking bots build vast knowledge bank |url=https://www.newscientist.com/article/mg22329832-700-googles-fact-checking-bots-build-vast-knowledge-bank/ |website=[[New Scientist]] |date=August 20, 2014 |accessdate=December 10, 2017}}</ref> After publication, Google reached out to ''[[Search Engine Land]]'' to explain that Knowledge Vault was a research paper, not an active Google service, and in its report, ''Search Engine Land'' referenced indications by the company that "numerous models" were being experimented with to examine the possibility of automatically gathering meaning from text.<ref>{{cite web |first=Greg |last=Sterling |title=Google "Knowledge Vault" To Power Future Of Search |url=https://searchengineland.com/google-builds-next-gen-knowledge-graph-future-201640 |website=[[Search Engine Land]] |date=August 25, 2014 |accessdate=December 10, 2017}}</ref>  The Knowledge Vault was meant to deal with facts, automatically gathering and merging information from across the Internet into a knowledge base capable of answering direct questions, such as "Where was [[Madonna (entertainer)|Madonna]] born". It was reported that its main ability over the Knowledge Graph was to gather information automatically rather than relying on crowd sourced facts compiled by humans; by the time of the 2014 report, it had collected over 1.6 billion facts, 271 million of which were considered "confident facts", a term for information deemed more than 90% true.

In August 2014, New Scientist reported that Google had launched Knowledge Vault. After publication, Google reached out to Search Engine Land to explain that Knowledge Vault was a research paper, not an active Google service, and in its report, Search Engine Land referenced indications by the company that "numerous models" were being experimented with to examine the possibility of automatically gathering meaning from text.  The Knowledge Vault was meant to deal with facts, automatically gathering and merging information from across the Internet into a knowledge base capable of answering direct questions, such as "Where was Madonna born". It was reported that its main ability over the Knowledge Graph was to gather information automatically rather than relying on crowd sourced facts compiled by humans; by the time of the 2014 report, it had collected over 1.6 billion facts, 271 million of which were considered "confident facts", a term for information deemed more than 90% true.

In August 2014, New Scientist reported that Google had launched Knowledge Vault. After publication, Google reached out to Search Engine Land to explain that Knowledge Vault was a research paper, not an active Google service, and in its report, Search Engine Land referenced indications by the company that "numerous models" were being experimented with to examine the possibility of automatically gathering meaning from text.  The Knowledge Vault was meant to deal with facts, automatically gathering and merging information from across the Internet into a knowledge base capable of answering direct questions, such as "Where was Madonna born". It was reported that its main ability over the Knowledge Graph was to gather information automatically rather than relying on crowd sourced facts compiled by humans; by the time of the 2014 report, it had collected over 1.6 billion facts, 271 million of which were considered "confident facts", a term for information deemed more than 90% true.

2014年8月，<font color=#32cd32>《新科学家》</font>杂志报道，谷歌启动了一个知识库项目。文章发表后，谷歌联系到“搜索引擎天地”，解释说知识库是一篇研究性论文，而不是谷歌的主动服务。在其报道中，“搜索引擎天地”提到，谷歌指出：他们在用“很多模型”探索从文本中自动收集语义的可能性。谷歌知识库旨在处理<font color="#32cd32">信息关系</font>，从互联网上自动收集和整合信息，形成一个能够直接回答诸如“麦当娜出生在哪里”等问题的知识库。2014年的一份报告指出，知识图谱聚合了超过16亿<font color=#32cd32>信息关系</font>，其中2.71亿被认为是“可信的事实”，被认为可信度超过90%。

2014年8月，<font color=#32cd32>《新科学家》</font>杂志报道，谷歌启动了一个知识库项目。文章发表后，谷歌联系到“搜索引擎天地”，解释说知识库是一篇研究性论文，而不是谷歌的主动服务。在其报道中，“搜索引擎天地”提到，谷歌指出：他们在用“很多模型”探索从文本中自动收集语义的可能性。谷歌知识库旨在处理<font color="#32cd32">信息关系</font>，从互联网上自动收集和整合信息，形成一个能够直接回答诸如“麦当娜出生在哪里”等问题的知识库。2014年的一份报告指出，知识图谱聚合了超过16亿<font color=#32cd32>信息关系</font>，其中2.71亿被认为是“可信的事实”，被认为可信度超过90%。