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Filling Knowledge Base Gaps for Distant Supervision of Relation Extraction

Wei Xu, Raphael Hoffmann, Le Zhao, Ralph Grishman
2013 Annual Meeting of the Association for Computational Linguistics  
Distant supervision has attracted recent interest for training information extraction systems because it does not require any human annotation but rather employs existing knowledge bases to heuristically  ...  Our proposed technique significantly improves the quality of distantly supervised relation extraction, boosting recall from 47.7% to 61.2% with a consistently high level of precision of around 93% in the  ...  , of AFRL, IARPA, DoI/NBC, or the U.S.  ... 
dblp:conf/acl/XuHZG13 fatcat:enpe4uy5onasxoeph3745kxhh4

Scalable Construction and Reasoning of Massive Knowledge Bases

Xiang Ren, Nanyun Peng, William Yang Wang
2018 Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts  
How to turn such massive and unstructured text data into structured, actionable knowledge for computational machines, and furthermore, how to teach machines learn to reason and complete the extracted knowledge  ...  In today's information-based society, there is abundant knowledge out there carried in the form of natural language texts (e.g., news articles, social media posts, scientific publications), which spans  ...  This tutorial also presents recent advances in applying distant and weak supervision to the extraction of structured facts in knowledge base construction, in addition to the traditional supervised techniques  ... 
doi:10.18653/v1/n18-6003 dblp:conf/naacl/RenPW18 fatcat:t57e7rwinjfbbgxzddcerishwi

FINDING OUT NOISY PATTERNS FOR RELATION EXTRACTION OF BANGLA SENTENCES

Rukaiya Habib
2020 Zenodo  
Freebase is a large collaborative knowledge base and database of general, structured information for public use. But for Bangla language, there is no available Freebase.  ...  The goal of the paper is to find out the noisy patterns for relation extraction of Bangla sentences.  ...  ACKNOWLEDGEMENTS We are thankful to the Department of Computer Science & Engineering, Jahangirnagar University.  ... 
doi:10.5281/zenodo.3700952 fatcat:lkxmjw2g35h2tgbchupi3alxde

Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction [article]

Qinyuan Ye, Liyuan Liu, Maosen Zhang, Xiang Ren
2019 arXiv   pre-print
In recent years there is a surge of interest in applying distant supervision (DS) to automatically generate training data for relation extraction (RE).  ...  To further validate our intuition, we develop a simple yet effective adaptation method for DS-trained models, bias adjustment, which updates models learned over the source domain (i.e., DS training set  ...  We would like to thank all the collaborators in INK research lab for their constructive feedback on the work.  ... 
arXiv:1904.09331v2 fatcat:676knvbzyjcovbh7y3lxsdl7fe

New York University 2012 System for KBP Slot Filling

Bonan Min, Xiang Li, Ralph Grishman, Ang Sun
2012 Text Analysis Conference  
We improved our distant-supervision based slot-filling component with a few techniques including filtering errors by statistical measures collected from the source corpus, and relabeling erroneous training  ...  After the formal evaluation we experimented with models for estimating slot confidence. We report on the impact of these changes.  ...  Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.  ... 
dblp:conf/tac/MinLGS12 fatcat:pxyq63fcdvabpgo7lwetrxwahy

Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction

Qinyuan Ye, Liyuan Liu, Maosen Zhang, Xiang Ren
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)  
In recent years there is a surge of interest in applying distant supervision (DS) to automatically generate training data for relation extraction (RE).  ...  To further validate our intuition, we develop a simple yet effective adaptation method for DS-trained models, bias adjustment, which updates models learned over the source domain (i.e., DS training set  ...  We would like to thank all the collaborators in INK research lab for their constructive feedback on the work.  ... 
doi:10.18653/v1/d19-1397 dblp:conf/emnlp/YeLZR19 fatcat:vyfqxgd5d5hlzd7dqlg4ud3ueq

Towards Understanding Gender Bias in Relation Extraction [article]

Andrew Gaut, Tony Sun, Shirlyn Tang, Yuxin Huang, Jing Qian, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, William Yang Wang
2020 arXiv   pre-print
Recent developments in Neural Relation Extraction (NRE) have made significant strides towards Automated Knowledge Base Construction (AKBC).  ...  We create WikiGenderBias, a distantly supervised dataset with a human annotated test set. WikiGenderBias has sentences specifically curated to analyze gender bias in relation extraction systems.  ...  Given a relation (e 1 , r, e 2 ) in a knowledge base (KB), distant supervision assumes any sentence that contains both e 1 and e 2 expresses r (Mintz et al., 2009 ).  ... 
arXiv:1911.03642v3 fatcat:accl32dppbbxzbesmfpj62bekm

TDJEE: A Document-Level Joint Model for Financial Event Extraction

Peng Wang, Zhenkai Deng, Ruilong Cui
2021 Electronics  
Furthermore, a Fonduer-based knowledge base combined with the distant supervision method is proposed to simplify the event labeling and provide high quality labeled training corpus for model training and  ...  To address this problem, this paper proposes a relation-aware Transformer-based Document-level Joint Event Extraction model (TDJEE), which encodes relations between words into the context and leverages  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/electronics10070824 fatcat:46rm3c2d7fa5jbumkao5uu3lhi

A Brief Review of Relation Extraction Based on Pre-Trained Language Models [chapter]

Tiange Xu, Fu Zhang
2020 Frontiers in Artificial Intelligence and Applications  
This review mainly summarizes the research progress of pre-trained language models such as BERT in supervised learning and distant supervision relation extraction.  ...  At present, the accuracy of relation extraction tasks based on pre-trained language models such as BERT exceeds the methods based on Convolutional or Recurrent Neural Networks.  ...  Acknowledgments The authors thank the anonymous referees for their valuable comments and suggestions. The work is supported by the National Natural Science Foundation of China (61672139).  ... 
doi:10.3233/faia200755 fatcat:3n7a5c4ze5chtljsrtzmd323pi

Finding out Noisy Patterns for Relation Extraction of Bangla Sentences

Rukaiya Habib, Md. Musfique Anwar
2020 International Journal on Natural Language Computing  
Freebase is a large collaborative knowledge base and database of general, structured information for public use. But for Bangla language, there is no available Freebase.  ...  The goal of the paper is to find out the noisy patterns for relation extraction of Bangla sentences.  ...  ACKNOWLEDGEMENTS We are thankful to the Department of Computer Science & Engineering, Jahangirnagar University.  ... 
doi:10.5121/ijnlc.2020.9102 fatcat:d4yxsc2tprdwhhpzlfr3ykg5cu

RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information [article]

Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga, Chiranjib Bhattacharyya, Partha Talukdar
2019 arXiv   pre-print
Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically aligning relation instances in a Knowledge Base (KB) with unstructured text.  ...  In this paper, we propose RESIDE, a distantly-supervised neural relation extraction method which utilizes additional side information from KBs for improved relation extraction.  ...  Acknowledgements We thank the anonymous reviewers for their constructive comments.  ... 
arXiv:1812.04361v2 fatcat:xorwrvmu4jhmjn67dyedohfhxe

RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information

Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga, Chiranjib Bhattacharyya, Partha Talukdar
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically aligning relation instances in a Knowledge Base (KB) with unstructured text.  ...  In this paper, we propose RESIDE, a distantly-supervised neural relation extraction method which utilizes additional side information from KBs for improved relation extraction.  ...  Acknowledgements We thank the anonymous reviewers for their constructive comments.  ... 
doi:10.18653/v1/d18-1157 dblp:conf/emnlp/VashishthJPBT18 fatcat:5fzlhteldzbedpoblowakpw2vy

Improving Distantly-Supervised Relation Extraction with Joint Label Embedding

Linmei Hu, Luhao Zhang, Chuan Shi, Liqiang Nie, Weili Guan, Cheng Yang
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)  
Distantly-supervised relation extraction has proven to be effective to find relational facts from texts.  ...  In this paper, we propose a novel multi-layer attention-based model to improve relation extraction with joint label embedding.  ...  Acknowledgement This work is supported by the National Natural Science Foundation of China (No. 61806020, 61772082, 61702296), the National Key Research and Development Program of China (2017YFB0803304  ... 
doi:10.18653/v1/d19-1395 dblp:conf/emnlp/HuZSNGY19 fatcat:u2sfr5p5pneodde5bkilbmxefa

H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation Extraction [article]

Jhih-Wei Chen, Tsu-Jui Fu, Chen-Kang Lee, Wei-Yun Ma
2020 arXiv   pre-print
We here propose H-FND, a hierarchical false-negative denoising framework for robust distant supervision relation extraction, as an FN denoising solution.  ...  Although distant supervision automatically generates training data for relation extraction, it also introduces false-positive (FP) and false-negative (FN) training instances to the generated datasets.  ...  Filling Knowledge Base Gaps for Distant Supervision of Relation Extraction.  ... 
arXiv:2012.03536v2 fatcat:h23uzydev5dd5iff3js77pwba4

Distant Supervised Relation Extraction with Cost-Sensitive Loss

Daojian Zeng, Yao Xiao, Jin Wang, Yuan Dai, Arun Kumar Sangaiah
2019 Computers Materials & Continua  
Recently, many researchers have concentrated on distant supervision relation extraction (DSRE).  ...  of imbalanced data sets under distant supervision.  ...  [Mintz, Bills, Snow et al. (2009) ] uses the freebase, a prevalent knowledge base, to align with rich unstructured data for distant supervision, so that a large amount of labeled data can be obtained.  ... 
doi:10.32604/cmc.2019.06100 fatcat:nw4qxrfrpvgwrk6jeajz4rjbae
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