Zero-shot relation triplet extraction (ZeroRTE) endeavors to extract relation triplets from a test
set using a model trained on a training set with disjoint relations from the test set. Current …

Extracting relations from a document is more challenging than from a sentence, due to the
involvement of more entities and complex contextual information. To capture long-distance …

Document-level relation extraction focuses on identifying the relations between entity pairs
across the entirety of a document. However, current mainstream methods mainly have two …

Extracting structured information from unstructured text is crucial for knowledge
management and utilization, which is the goal of document-level relation extraction. Existing …

Relation extraction is the process of identifying connections between entities in unstructured
text and is a critical component of entity-centred information extraction to uncover latent …

Knowledge Bases (KBs) have become more complex because some facts in KBs include
more than two entities. The construction and completion of these KBs require a new relation …

The task of document-level relation extraction is the classification of the relations between
pairs of entities within a document. The identification of relations between inter-sentence …

Document-level relation extraction extracts relations between entity pairs from multiple
sentences in a document by reasoning about semantic relationships between entities and …

Document-level relation extraction aims to uncover relations between entities by harnessing
the intricate information spread throughout a document. Previous research involved …

Detecting relations between entities across multiple sentences in a document, referred to as
document-level relation extraction, poses a challenge in natural language processing …