A comprehensive survey on automatic knowledge graph construction
Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …
knowledge. To this end, much effort has historically been spent extracting informative fact …
A survey on neural relation extraction
K Liu - Science China Technological Sciences, 2020 - Springer
Relation extraction is a key task for knowledge graph construction and natural language
processing, which aims to extract meaningful relational information between entities from …
processing, which aims to extract meaningful relational information between entities from …
Document-level event causality identification via graph inference mechanism
Event causality identification is an important research task in natural language processing.
Existing methods largely focus on identifying explicit causal relations, and give poor …
Existing methods largely focus on identifying explicit causal relations, and give poor …
Active relation discovery: Towards general and label-aware open relation extraction
Abstract Open Relation Extraction (OpenRE) aims to discover novel relations from open
domains. Previous OpenRE methods mainly suffer from two problems:(1) Insufficient …
domains. Previous OpenRE methods mainly suffer from two problems:(1) Insufficient …
TP-DDI: Transformer-based pipeline for the extraction of Drug-Drug Interactions
Abstract Drug-Drug Interaction (DDI) extraction is the task of identifying drug entities and the
potential interactions between drug pairs from biomedical literature. Computer-aided …
potential interactions between drug pairs from biomedical literature. Computer-aided …
Semantic Relation Extraction: A Review of Approaches, Datasets, and Evaluation Methods With Looking at the Methods and Datasets in the Persian Language
A large volume of unstructured data, especially text data, is generated and exchanged daily.
Consequently, the importance of extracting patterns and discovering knowledge from textual …
Consequently, the importance of extracting patterns and discovering knowledge from textual …
Entity and evidence guided relation extraction for docred
Document-level relation extraction is a challenging task which requires reasoning over
multiple sentences in order to predict relations in a document. In this paper, we pro-pose a …
multiple sentences in order to predict relations in a document. In this paper, we pro-pose a …
Modeling multi-granularity hierarchical features for relation extraction
Relation extraction is a key task in Natural Language Processing (NLP), which aims to
extract relations between entity pairs from given texts. Recently, relation extraction (RE) has …
extract relations between entity pairs from given texts. Recently, relation extraction (RE) has …
BioGSF: a graph-driven semantic feature integration framework for biomedical relation extraction
Y Yang, Z Zheng, Y Xu, H Wei… - Briefings in …, 2025 - academic.oup.com
The automatic and accurate extraction of diverse biomedical relations from literature
constitutes the core elements of medical knowledge graphs, which are indispensable for …
constitutes the core elements of medical knowledge graphs, which are indispensable for …
Complex relation extraction: Challenges and opportunities
H Jiang, Q Bao, Q Cheng, D Yang, L Wang… - arxiv preprint arxiv …, 2020 - arxiv.org
Relation extraction aims to identify the target relations of entities in texts. Relation extraction
is very important for knowledge base construction and text understanding. Traditional binary …
is very important for knowledge base construction and text understanding. Traditional binary …