Results 21 to 30 of about 5,797,629 (324)
A Frustratingly Easy Approach for Entity and Relation Extraction
North American Chapter of the Association for Computational Linguistics, 2021 End-to-end relation extraction aims to identify named entities and extract relations between them. Most recent work models these two subtasks jointly, either by casting them in one structured prediction framework, or performing multi-task learning ...
Zexuan Zhong, Danqi Chen
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OneRel: Joint Entity and Relation Extraction with One Module in One Step [PDF]
AAAI Conference on Artificial Intelligence, 2022 Joint entity and relation extraction is an essential task in natural language processing and knowledge graph construction. Existing approaches usually decompose the joint extraction task into several basic modules or processing steps to make it easy to ...
Yu-Ming Shang +2 more
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Entropy, 2023 Implicit discourse relation recognition (IDRR) has long been considered a challenging problem in shallow discourse parsing. The absence of connectives makes such relations implicit and requires much more effort to understand the semantics of the text ...
Zhongyang Fang +5 more
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Enhancing Multimodal Entity and Relation Extraction With Variational Information Bottleneck [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2023 This article studies the multimodal named entity recognition (MNER) and multimodal relation extraction (MRE), which are important for content analysis and various applications.
Shiyao Cui +6 more
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BioRED: a rich biomedical relation extraction dataset [PDF]
Briefings Bioinform., 2022 Automated relation extraction (RE) from biomedical literature is critical for many downstream text mining applications in both research and real-world settings.
Ling Luo +4 more
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A Study on Double-Headed Entities and Relations Prediction Framework for Joint Triple Extraction
Mathematics, 2023 Relational triple extraction, a fundamental procedure in natural language processing knowledge graph construction, assumes a crucial and irreplaceable role in the domain of academic research related to information extraction.
Yanbing Xiao +6 more
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Chinese Relation Extraction Using Extend Softword
IEEE Access, 2021 In recent years, many scholars have chosen to use word lexicons to incorporate word information into a model based on character input to improve the performance of Chinese relation extraction (RE). For example, Li et al.
Bo Kong +4 more
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Towards relation extraction from speech
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 Relation extraction typically aims to extract semantic relationships between entities from the unstructured text. One of the most essential data sources for relation extraction is the spoken language, such as interviews and dialogues. However, the error propagation introduced in automatic speech recognition (ASR) has been ignored in relation extraction,
Wu, Tongtong +6 more
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Exploiting sequence labeling framework to extract document-level relations from biomedical texts
BMC Bioinformatics, 2020 Background Both intra- and inter-sentential semantic relations in biomedical texts provide valuable information for biomedical research. However, most existing methods either focus on extracting intra-sentential relations and ignore inter-sentential ones
Zhiheng Li +5 more
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DocRED: A Large-Scale Document-Level Relation Extraction Dataset [PDF]
Annual Meeting of the Association for Computational Linguistics, 2019 Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs.
Yuan Yao +9 more
semanticscholar +1 more source