Relation extraction is a crucial step in the constructions of knowledge graphs (KGs).
However, relation extraction is performed manually in the manufacturing field due to the …

As an essential task in the field of knowledge graph, relation extraction (RE) has received
extensive attention from researchers. Since the existing RE methods only adopt one trained …

With the widespread use of big data, knowledge graph has become a new hotspot. It is used
in intelligent question answering, recommendation system, map navigation and so on …

Relation extraction (RE) aims at extracting the relation between two entities from the text
corpora. It is a crucial task for Knowledge Graph (KG) construction. Most existing methods …

Joint extraction of entities and relations is to recognize entities and semantic relations
simultaneously, which is significant for knowledge graph construction. Recently, many …

Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting
entity relations from texts. However, it usually suffers from the long-tail issue. The training …

Joint entity and relation extraction is a fundamental and important task in the process of
building knowledge graphs. At present, many researchers have proposed their own …

Semantic relation extraction is crucial to automatically constructing a knowledge graph (KG),
and it supports a variety of downstream natural language processing (NLP) tasks such as …

Relation extraction is an important processing task in knowledge graph completion. In
previous approaches, it is considered to be a multi-class classification problem. In this …

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 …