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Extraction and grammatical relations

Lingua, 1988
Abstract The paper offers a new approach to extraction structures (topicalisation, wh -movement, etc.), in which all the work is done by grammatical relations. The analysis is based on Word Grammar, so the grammatical relations between the extracted item and its ‘true’ head are shown directly. The relations between its surface position and this word
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Neuro-Symbolic Relation Extraction

Neuro-symbolic relation extraction lies at the intersection of neural networks and symbolic reasoning, presenting promising opportunities to enhance the capabilities of natural language processing (NLP) systems. Despite its potential, a comprehensive review of how these systems are developed and applied to the task of relation extraction has been ...
Yan, Xi   +4 more
openaire   +2 more sources

Key Relation Extraction from Biomedical Publications

2017
Within the large body of biomedical knowledge, recent findings and discoveries are most often presented as research articles. Their number has been increasing sharply since the turn of the century, presenting ever-growing challenges for search and discovery of knowledge and information related to specific topics of interest, even with the help of ...
Lan, Huang   +4 more
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Overview of Relation Extraction

2021 International Conference on Advanced Computing and Endogenous Security, 2022
Xuhui Song   +4 more
openaire   +1 more source

Pattern-Based Relation Extraction

2016
The chapter looks into pattern-based approaches to relation extraction in text, with an underlying purpose of knowledge base expansion. As pattern-based approaches require explicit mentions of relations in text, the chapter discusses the interdependency between relations and text types.
openaire   +1 more source

Deep Neural Approaches to Relation Triplets Extraction: a Comprehensive Survey

Cognitive Computation, 2021
Tapas Nayak, Pawan Goyal, Soujanya Poria
exaly  

Named Entity Recognition and Relation Extraction

ACM Computing Surveys, 2022
Zara Nasar   +2 more
exaly  

BioRED: a rich biomedical relation extraction dataset

Briefings in Bioinformatics, 2022
Ling Luo, Po-Ting Lai, Chih-Hsuan Wei
exaly  

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