Document-level relation extraction aims to extract relations among multiple entity pairs from a document. Previously proposed graph-based or transformer-based models utilize the …
Multimodal named entity recognition and relation extraction (MNER and MRE) is a fundamental and crucial branch in information extraction. However, existing approaches for …
Triple extraction is an essential task in information extraction for natural language processing and knowledge graph construction. In this paper, we revisit the end-to-end triple …
We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the …
Information Extraction (IE) aims to extract structural information from unstructured texts. In practice, long-tailed distributions caused by the selection bias of a dataset, may lead to …
S Deng, C Wang, Z Li, N Zhang, Z Dai… - 2023 IEEE 39th …, 2023 - ieeexplore.ieee.org
Business Knowledge Graphs (KGs) are important to many enterprises today, providing factual knowledge and structured data that steer many products and make them more …
Information extraction tasks such as entity relation extraction and event extraction are of great importance for natural language processing and knowledge graph construction. In this …
Event understanding aims at understanding the content and relationship of events within texts, which covers multiple complicated information extraction tasks: event detection, event …
Extraction of Application Programming Interfaces (APIs) and their semantic relations from unstructured text (eg, Stack Overflow) is a fundamental work for software engineering tasks …