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OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
[article]
2019
arXiv
pre-print
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OpenNRE is an open-source and extensible toolkit that provides a unified framework to implement neural models for relation extraction (RE). ...
Besides the toolkit, we also release an online system to meet real-time extraction without any training and deploying. ...
Conclusion We propose OpenNRE, an open and extensible toolkit for relation extraction. ...
arXiv:1909.13078v1
fatcat:pda6f5abobasteuwyr32jignty
OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
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OpenNRE is an open-source and extensible toolkit that provides a unified framework to implement neural models for relation extraction (RE). ...
Besides the toolkit, we also release an online system to meet real-time extraction without any training and deploying. ...
Conclusion We propose OpenNRE, an open and extensible toolkit for relation extraction. ...
doi:10.18653/v1/d19-3029
dblp:conf/emnlp/HanGYYLS19
fatcat:bk6gv4b5ufc6fbzdnulbhcvbp4
Resources
[chapter]
2020
Representation Learning for Natural Language Processing
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However, training a deep neural network is usually a very time-intensive process and requires lots of code to build related models. ...
In this chapter, we aim to exhibit features and running performance of these frameworks so that users can select an appropriate framework for their usage. ...
Open Resources for Knowledge Graph Representation
OpenKE OpenKE 10 [2] is an open-source toolkit for Knowledge Embedding (KE), which provides a unified framework and various fundamental KE models. ...
doi:10.1007/978-981-15-5573-2_10
fatcat:qs6uihkvjnfmndbdtr32buqt7y
DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
[article]
2022
arXiv
pre-print
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We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population. ...
Besides, we present an online system in http://deepke.openkg.cn/EN/re_doc_show.html for real-time extraction of various tasks, and a demo video. ...
Acknowledgments We want to express gratitude to the anonymous reviewers for their kind comments. ...
arXiv:2201.03335v5
fatcat:4az44xcuzzgqbo4w4e7kfcqz3u
TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation Extraction
2022
BMC Bioinformatics
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However, most of them are populated and updated with a great deal of human effort. Biomedical Relation Extraction (BioRE) aims to shift this burden to machines. ...
We have evaluated state-of-the-art models for GDA extraction on TBGA, showing that it is a challenging and well-suited dataset for the task. ...
We built models using OpenNRE [35] , an open and extensible toolkit for Neural Relation Extraction (NRE). ...
doi:10.1186/s12859-022-04646-6
pmid:35361129
pmcid:PMC8973894
fatcat:gf4qv3snlze2tf2zlxbljsapfu
More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction
[article]
2020
arXiv
pre-print
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In order to extract these facts from text, people have been working on relation extraction (RE) for years. ...
, efficiently learn more relations, easily handle more complicated context, and flexibly generalize to more open domains. ...
Acknowledgments This work is supported by the Natural Science Foundation of China (NSFC) and the German Research Foundation (DFG) in Project Crossmodal Learning, NSFC 61621136008 / DFG TRR-169, and Beijing ...
arXiv:2004.03186v3
fatcat:old3zax3fjauvf5fgsvjwakv2i
Exploring the Suitability of Semantic Spaces as Word Association Models for the Extraction of Semantic Relationships
[article]
2020
arXiv
pre-print
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of relationships to be considered for extraction. ...
with relation extraction approaches. ...
In fact, we used OpenNRE as an open-source and extensible toolkit that provides a unified framework to implement relation extraction models. ...
arXiv:2004.14265v1
fatcat:mxr47hf3xnf4fjhbnowff75tsa
Neural relation extraction: a review
2020
Turkish Journal of Electrical Engineering and Computer Sciences
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Conventional neural models for relation extraction 15 Recent research studies focus on extracting relational features with neural networks instead of manual work 16 [41, 46, 67]. ...
various approaches on data expressiveness for relation extraction. ...
Opennre: An open and extensible toolkit for neural 36 relation extraction. arXiv preprint arXiv:1909.13078. 37 [21] Han, X., Liu, Z., and Sun, M. (2018a). ...
doi:10.3906/elk-2005-119
fatcat:o36duadbunhmbesuyayc5jfmxe
PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction
[article]
2022
arXiv
pre-print
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Neural models for distantly supervised relation extraction (DS-RE) encode each sentence in an entity-pair bag separately. These are then aggregated for bag-level relation prediction. ...
The contextual embeddings of tokens are aggregated using attention with the candidate relation as query -- this summary of whole passage predicts the candidate relation. ...
We thank Abhyuday Bhartiya for helping in reproducing results from the DiS-ReX paper, and Keshav Kolluru for helpful comments on an earlier draft of the paper. ...
arXiv:2110.07415v2
fatcat:ing2hsgkyrdtfjdx2xpgo6d6ga
Towards Realistic Low-resource Relation Extraction: A Benchmark with Empirical Baseline Study
[article]
2023
arXiv
pre-print
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2022 pre-print arXiv:2210.10678v2 fatcat:q357lfvu2jbp7bav725nyekpd4Other Versions
This paper presents an empirical study to build relation extraction systems in low-resource settings. ...
We create a benchmark with 8 relation extraction (RE) datasets covering different languages, domains and contexts and perform extensive comparisons over the proposed schemes with combinations. ...
Acknowledgment We would like to express gratitude to the anonymous reviewers for their kind comments. ...
arXiv:2210.10678v3
fatcat:gs2sktbbsne4jn62od6mgxwloa
A Data-driven Approach for Noise Reduction in Distantly Supervised Biomedical Relation Extraction
[article]
2020
arXiv
pre-print
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reduces noise, reaching state-of-the-art performance for distantly-supervised biomedical relation extraction. ...
Our approach further encodes knowledge about the direction of relation triples, allowing for increased focus on relation learning by reducing noise and alleviating the need for joint learning with knowledge ...
Acknowledgements The authors would like to thank the anonymous reviewers for helpful feedback. ...
arXiv:2005.12565v1
fatcat:me4hvynjlbfixd74f2tlg65c3a
A Comprehensive Survey on Automatic Knowledge Graph Construction
[article]
2023
arXiv
pre-print
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The survey concludes with discussions on the challenges and possible directions for future exploration. ...
The survey covers models for knowledge refinement, including knowledge graph completion, and knowledge fusion. ...
OpenNRE [67] provides various extensible neural network models such as CNN and LSTM to perform supervised relation extraction. Deep learning toolkits provide high-performance techniques for users. ...
arXiv:2302.05019v1
fatcat:7in54wjwyzhfnkx755izrkzr3y
A Simple but Effective Approach to Improve Structured Language Model Output for Information Extraction
[article]
2024
arXiv
pre-print
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extraction (RE). ...
To address this issue, this paper introduces an efficient method, G&O, to enhance their structured text generation capabilities. ...
Acknowledgments This work was supported in part by NSF IIS-2008334, IIS-2144338, and ONR MURI N00014-17-1-2656. ...
arXiv:2402.13364v1
fatcat:mzz37xv6lrcf5g3i5j2mxiydni
A Survey on Knowledge Graphs: Representation, Acquisition and Applications
[article]
2021
IEEE Transactions on Neural Networks and Learning Systems
accepted
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Knowledge graphs that represent structural relations between entities have become an increasingly popular research direction towards cognition and human-level intelligence. ...
For knowledge acquisition, especially knowledge graph completion, embedding methods, path inference, and logical rule reasoning, are reviewed. ...
Notably, there are three useful toolkits, namely scikit-kge and OpenKE [253] for knowledge graph embedding, and OpenNRE [254] for relation extraction. ...
doi:10.1109/tnnls.2021.3070843
pmid:33900922
arXiv:2002.00388v4
fatcat:4l2yxnf3wbg4zpzdumduvyr4he
CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet
2021
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
unpublished
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Third, for extensibility, owing to the design of three-tier architecture, CogIE is not only a plug-and-play toolkit for developers but also an extensible programming framework for researchers. ...
We release an open-access online system 1 to visually extract information from texts. ...
Acknowledgments This work is supported by the National Key Research and Development Program of China (No. 2020AAA0106400), the National Natural Science Foundation of China (No.61806201). ...
doi:10.18653/v1/2021.acl-demo.11
fatcat:3yiphl7e2nek5ooonb2q3tm2fa
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