EmRel: joint representation of entities and embedded relations for multi-triple extraction
Multi-triple extraction is a challenging task due to the existence of informative inter-triple
correlations, and consequently rich interactions across the constituent entities and relations …
correlations, and consequently rich interactions across the constituent entities and relations …
Joint extraction of entities and relations via an entity correlated attention neural model
Named entity recognition and relation extraction are crucial tasks in natural language
processing. As the traditional pipelined manners may suffer from the error propagation issue …
processing. As the traditional pipelined manners may suffer from the error propagation issue …
Effective cascade dual-decoder model for joint entity and relation extraction
Extracting relational triples from texts is a fundamental task in knowledge graph construction.
The popular way of existing methods is to jointly extract entities and relations using a single …
The popular way of existing methods is to jointly extract entities and relations using a single …
A novel tensor learning model for joint relational triplet extraction
Z Wang, H Nie, W Zheng, Y Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The relational triplet is a format to represent relational facts in the real world, which consists
of two entities and a semantic relation between these two entities. Since the relational triplet …
of two entities and a semantic relation between these two entities. Since the relational triplet …
TW-Net: Transformer weighted network for neonatal brain MRI segmentation
Accurate neonatal brain MRI segmentation is valuable for investigating brain growth
patterns and tracking the progression of neurodevelopmental disorders. However, it is a …
patterns and tracking the progression of neurodevelopmental disorders. However, it is a …