Document-level relation extraction (DocRE) poses the challenge of identifying relationships
between entities within a document. Existing approaches rely on logical reasoning or …

Document-level relation extraction (RE) aims to identify the relations between entities
throughout an entire document. It needs complex reasoning skills to synthesize various …

We study the data sparsity problem for data generated from an integration system. We
approach the problem from a textual information extraction perspective and propose to …

While being an important pillar of human society, legal domain consists of large corpora of
complex documents about different aspects such as laws or court judgements. In recent …

Relation extraction (RE) is a well-known NLP application often treated as a sentence-or
document-level task. However, a handful of recent efforts explore it across documents or in …

Abstract Knowledge is the lifeblood for a plethora of applications such as search,
recommender systems and natural language understanding. Thanks to the efforts in the …

Abstract Knowledge graphs (KGs) have been playing a crucial role in leveraging information
on web for several downstream tasks. Despite previous efforts in populating KGs, these …

Relation extraction is the task of extracting relationships from input text, where input can be a
sentence, document, or multiple documents. This task has been popular for decades and is …

Аннотация Рассматривается задача оценки доверия к информации, извлекаемой из
текстовых источников для пополнения онтологий или графов знаний. За единицу …

Abstract Knowledge graphs (KG), which are structures representing information
corresponding to entities/topics and their inter-connections, have been playing a crucial role …