With the advent of Web 2.0, there exist many online platforms that result in massive textual-
data production. With ever-increasing textual data at hand, it is of immense importance to …

Abstract Knowledge is a formal way of understanding the world, providing human-level
cognition and intelligence for the next-generation artificial intelligence (AI). An effective way …

Relation classification is a crucial ingredient in numerous information extraction systems
seeking to mine structured facts from text. We propose a novel convolutional neural network …

The state-of-the-art methods used for relation classification are primarily based on statistical
machine learning, and their performance strongly depends on the quality of the extracted …

实体关系抽取作为信息抽取, 自然语言理解, 信息检索等领域的核心任务和重要环节,
能够从文本中抽取实体对间的语义关系. 近年来, 深度学习在联合学习, 远程监督等方面上的应用 …

The large number of potential applications from bridging web data with knowledge bases
have led to an increase in the entity linking research. Entity linking is the task to link entity …

Traditional relation extraction predicts relations within some fixed and finite target schema.
Machine learning approaches to this task require either manual annotation or, in the case of …

With the advent of the Internet, large amount of digital text is generated everyday in the form
of news articles, research publications, blogs, question answering forums and social media …

Semantic taxonomies such as WordNet provide a rich source of knowl-edge for natural
language processing applications, but are expensive to build, maintain, and extend …

Methods and systems for providing start and stop properties to Semantic Web structured
resources and statements are disclosed. The start and stop properties can specify a lifetime …