Relation classification is an important NLP task to extract relations between entities. The
state-of-the-art methods for relation classification are primarily based on Convolutional or …

Field compliance checking aims to check the compliance of site operations with applicable
construction safety regulations for detecting violations. Relation extraction provides an …

Background: Knowledge is evolving over time, often as a result of new discoveries or
changes in the adopted methods of reasoning. Also, new facts or evidence may become …

Chinese relation extraction is conducted using neural networks with either character-based
or word-based inputs, and most existing methods typically suffer from segmentation errors …

Knowledge, data, algorithms and computing power are the foundations of artificial
intelligence (AI), for which knowledge is the most powerful support. An effective way to …

A large majority of approaches have been proposed to leverage the dependency tree in the
relation classification task. Recent works have focused on pruning irrelevant information …

Relation extraction studies the issue of predicting semantic relations between pairs of
entities in sentences. Attention mechanisms are often used in this task to alleviate the inner …

As an essential part of artificial intelligence, a knowledge graph describes the real-world
entities, concepts and their various semantic relationships in a structured way and has been …

Document-level relation extraction (RE) is a more challenging task providing a new
perspective to solve larger and more complex text mining work. Recent document-level RE …

Many attempts have been made to construct new domain-specific knowledge graphs using
the existing knowledge base of various domains. However, traditional “dictionary-based” or …