Capturing Meaning: Toward an Abstract Wikipedia
Capturing Meaning: Toward an Abstract Wikipedia
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捕捉意义：迈向抽象维基百科
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发表时间：
2018
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通讯作者：
Denny Vrandečić
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作者：
Denny Vrandečić
语义Web语言允许以一种特别适合Web的方式表达本体和知识库。本体形式化了对领域的共同理解。但是我们所知道的最有表现力和最广泛的语言是人类的自然语言，我们拥有的最大的知识库是用人类语言写的丰富的文本。本文旨在寻找一条弥合OWL等知识表示语言与英语等人类自然语言之间鸿沟的途径。我们提出了一个项目来同时揭露这一差距，允许合作来缩小它，使进展广泛可见，并且本身就具有很高的吸引力和价值：一个用抽象语言编写的维基百科，可以根据要求翻译成任何自然语言。这将使当前维基百科编辑的生产力提高约100倍，并将维基百科的内容增加10倍。对于数十亿用户来说，这将解锁他们目前无法获得的知识。
Semantic Web languages allow to express ontologies and knowledge bases in a way meant to be particularly amenable to the Web. Ontologies formalize the shared understanding of a domain. But the most expressive and widespread languages that we know of are human natural languages, and the largest knowledge base we have is the wealth of text written in human languages. This paper looks for a path to bridge the gap between knowledge representation languages such as OWL and human natural languages such as English. We propose a project to simultaneously expose that gap, allow to collaborate on closing it, make progress widely visible, and is highly attractive and valuable in its own right: a Wikipedia written in an abstract language to be rendered into any natural language on request. This would make current Wikipedia editors about 100x more productive, and increase the content of Wikipedia by 10x. For billions of users this will unlock knowledge they currently do not have access to.