The Fintech mobile payment platform is expanding rapidly; this expansion, in turn, creates
numerous risks. There is an urgent need to better understand these risks and to spur more …

Recent work for extracting relations from texts has achieved excellent performance.
However, most existing methods pay less attention to the efficiency, making it still …

В статье представлена постановка задачи открытого извлечения информации.
Выполнен аналитический обзор работ в этой области, а также обзор смежных работ …

Legal ontologies have proved their increasingly substantial role in representing, processing
and retrieving legal information. By using the knowledge modeled by such ontologies in …

Being the intersection between lexical and computational science, Natural Language
Processing (NLP) has been earning a vast amount of attention in the past years. Relation …

Relation extraction is a subtask of natural langage processing that has seen many
improvements in recent years, with the advent of complex pre-trained architectures. Many of …

In this paper we discuss open information extraction from natural language texts. We present
an approach to extraction of semantic relationships using unsupervised machine learning …

Most of the previous works on relation extraction between named entities are often limited to
extracting the pre-defined types; which are inefficient for massive unlabeled text data …

With recent deep learning advances in natural language processing, tasks such as relation
extraction have been solved on benchmark data with near-perfect accuracy. However, in a …

In this paper, we propose a prototype question-answering system that works on top of an
automatically generated knowledge base. The knowledge base is constructed using …