Named entity relation extraction is an important subject in the field of information extraction.
Although many English extractors have achieved reasonable performance, an effective …

In today's big data era, there are a large number of unstructured information resources on
the web. Natural language processing researchers have been working hard to figure out …

To recognize errors in the power equipment defect records in real time, we propose an error
recognition method based on knowledge graph technology. According to the characteristics …

Abstract Open Relation Extraction (ORE) overcomes the limitations of traditional IE
techniques, which train individual extractors for every single relation type. Systems such as …

Featured Application Knowledge extraction technology can be applied to many scenarios,
such as factual knowledge graph construction. By using knowledge extraction technology …

The goal of relation extraction is to detect relations between two entities in free text. In a
sentence, a relation instance usually comprises a small number of words, which yields a …

Chinese is an ancient hieroglyphic. It is inattentive to structure. Therefore, segmenting and
parsing Chinese are more difficult and less accurate. In this paper, we propose an …

Relation extraction refers to a method of efficiently detecting and identifying predefined
semantic relationships within a set of entities in text documents. Numerous relation …

A story may be analyzed to identify the main characters and to extract the relationship
between them. Relation extraction problems are generally solved either through supervised …

Distantly supervised relation extraction has been widely used to find novel relational facts
between entities from text, and can be easily scaled to very large corpora. Previous studies …