Results 281 to 290 of about 1,302,763 (303)

Open Hierarchical Relation Extraction

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
Open relation extraction (OpenRE) aims to extract novel relation types from open-domain corpora, which plays an important role in completing the relation schemes of knowledge bases (KBs). Most OpenRE methods cast different relation types in isolation without considering their hierarchical dependency.
Kai Zhang, Yuan Yao, Ruobing Xie, Xu Han, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun   +7 more
openaire   +1 more source

Ontology-Aware Biomedical Relation Extraction

2022
MotivationAutomatically extracting relationships from biomedical texts among multiple sorts of entities is an essential task in biomedical natural language processing with numerous applications, such as drug development or repurposing, precision medicine, and other biomedical tasks requiring knowledge discovery. Current Relation Extraction (RE) systems
Ahmad Aghaebrahimian, Maria Anisimova, Manuel Gil   +2 more
openaire   +1 more source

Extractive Relations

2017
Extractive Relations explores the nature of industrial power and its role in shaping what we understand to be the global mining sector. The authors examine issues at the forefront of contemporary debates: corporate obligations in safeguarding the rights of people displaced by mining, the recognition of community rights and interests in supporting or ...
Owen, John R., Kemp, Deanna
openaire   +2 more sources

Document-level Relation Extraction with Relation Correlations

Neural Networks
Document-level relation extraction faces two often overlooked challenges: long-tail problem and multi-label problem. Previous work focuses mainly on obtaining better contextual representations for entity pairs, hardly address the above challenges. In this paper, we analyze the co-occurrence correlation of relations, and introduce it into the document ...
Ridong Han, Tao Peng, Benyou Wang, Lu Liu, Prayag Tiwari, Xiang Wan   +5 more
openaire   +2 more sources

Extracting multi-dimensional relations

Proceedings of the 20th ACM international conference on Information and knowledge management, 2011
Extracting relations among different entities from various data sources has been an important topic in data mining. While many methods focus only on a single type of relations, real world entities maintain relations that contain much richer information.
Ching-man Au Yeung, Tomoharu Iwata
openaire   +1 more source

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, Usmanova, Aida, Möller, Cedric, Westphal, Patrick, Usbeck, Ricardo   +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, Ye, Wang, Leiguang, Gong, Casimir, Kulikowski, Tian, Bai   +4 more
openaire   +2 more sources

Overview of Relation Extraction

2021 International Conference on Advanced Computing and Endogenous Security, 2022
Xuhui Song, Hongtao Yu, Shaomei Li, Xinbang Hu, Huansha Wang   +4 more
openaire   +1 more source