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From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading Comprehension [article]

Lingyong Yan, Xianpei Han, Le Sun, Fangchao Liu, Ning Bian
2020 arXiv   pre-print
In this paper, we propose a new DS paradigm–document-based distant supervision, which models relation extraction as a document-based machine reading comprehension (MRC) task.  ...  Distant supervision (DS) is a promising approach for relation extraction but often suffers from the noisy label problem.  ...  Document-based Distant Supervision via Machine Reading Comprehension This section describes our document-based DS paradigm.  ... 
arXiv:2012.04334v2 fatcat:4ab72nh2vfdrtddlrg5qienc2u

Neural relation extraction: a review

2020 Turkish Journal of Electrical Engineering and Computer Sciences  
Quirk 4 and Poon [36] are the first to address this problem in distantly supervised setups and proposed a document-level 5 graph representation to extract more relations.  ...  Supervised relation extraction 11 In supervised neural relation extraction from text the sentence-level relation extraction approach is adopted, 12 which requires training data with relational tags.  ...  Label-free 30 distant supervision for relation extraction via knowledge graph embedding.  ... 
doi:10.3906/elk-2005-119 fatcat:o36duadbunhmbesuyayc5jfmxe

Making Efficient Use of a Domain Expert's Time in Relation Extraction [article]

Linara Adilova, Sven Giesselbach, Stefan Rüping
2018 arXiv   pre-print
This is particularly true in relation extraction in text mining, where large corpora of texts exists in many application domains, while labeling of text data requires an expert to invest much time to read  ...  Distant supervision provides a mean of labeling data given known relations in a knowledge base, but it suffers from noisy labeling.  ...  Acknowledgements: This work upon which this paper is based was supported by means of the Bundesministerium für Bildung und Forschung (Förderkennzeichen 031L0025C).  ... 
arXiv:1807.04687v1 fatcat:xalliyi3wvhzbijxi3jwi77ty4

Type-Aware Distantly Supervised Relation Extraction with Linked Arguments

Mitchell Koch, John Gilmer, Stephen Soderland, Daniel S. Weld
2014 Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)  
We evaluate sentential extraction performance on two datasets: the popular set of NY Times articles partially annotated by Hoffmann et al. (2011) and a new dataset, called GORECO, that is comprehensively  ...  of linked arguments, and partitioning the model by relation type signature.  ...  This work was supported by Defense Advanced Research Projects Agency (DARPA) Machine Reading Program under Air Force Research Laboratory (AFRL) prime contract no.  ... 
doi:10.3115/v1/d14-1203 dblp:conf/emnlp/KochGSW14 fatcat:kguk566afnd4jaelcx2aju37eu

Deep Neural Networks for Relation Extraction [article]

Tapas Nayak
2021 arXiv   pre-print
Relation extraction from text is an important task for automatic knowledge base population.  ...  Finally, we propose a hierarchical entity graph convolutional network for relation extraction across documents.  ...  They modified the machine-reading comprehension models to a sequence tagging model so that they can find multiple answers to a question.  ... 
arXiv:2104.01799v1 fatcat:vmatz7gxazd4xnm2oprncd5mm4

Automating risk of bias assessment for clinical trials

Iain J. Marshall, Joël Kuiper, Byron C. Wallace
2014 Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14  
sentences from articles to support their bias assessments.  ...  We demonstrate that systematic reviews may be used to distantly supervise text mining models, obviating the need for manually annotated clinical trial reports.  ...  Concerning the sentence identification task, we used quotations from Cochrane as (distantly supervised) training and test data.  ... 
doi:10.1145/2649387.2649406 dblp:conf/bcb/MarshallKW14 fatcat:mydf3uuxibay5oniumetoeawuy

Automating Risk of Bias Assessment for Clinical Trials

Iain J Marshall, Joel Kuiper, Byron C Wallace
2015 IEEE journal of biomedical and health informatics  
sentences from articles to support their bias assessments.  ...  We demonstrate that systematic reviews may be used to distantly supervise text mining models, obviating the need for manually annotated clinical trial reports.  ...  Concerning the sentence identification task, we used quotations from Cochrane as (distantly supervised) training and test data.  ... 
doi:10.1109/jbhi.2015.2431314 pmid:25966488 fatcat:7ke6fe47hzgmzdox6jd3hfgnmy

Reading Wikipedia to Answer Open-Domain Questions [article]

Danqi Chen, Adam Fisch, Jason Weston, Antoine Bordes
2017 arXiv   pre-print
This task of machine reading at scale combines the challenges of document retrieval (finding the relevant articles) with that of machine comprehension of text (identifying the answer spans from those articles  ...  Our experiments on multiple existing QA datasets indicate that (1) both modules are highly competitive with respect to existing counterparts and (2) multitask learning using distant supervision on their  ...  Acknowledgments The authors thank Pranav Rajpurkar for testing Document Reader on the test set of SQuAD.  ... 
arXiv:1704.00051v2 fatcat:4eyc5giekzhg3eaa5jvgrmqvdu

Reading Wikipedia to Answer Open-Domain Questions

Danqi Chen, Adam Fisch, Jason Weston, Antoine Bordes
2017 Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
This task of machine reading at scale combines the challenges of document retrieval (finding the relevant articles) with that of machine comprehension of text (identifying the answer spans from those articles  ...  Our experiments on multiple existing QA datasets indicate that (1) both modules are highly competitive with respect to existing counterparts and (2) multitask learning using distant supervision on their  ...  Acknowledgments The authors thank Pranav Rajpurkar for testing Document Reader on the test set of SQuAD.  ... 
doi:10.18653/v1/p17-1171 dblp:conf/acl/ChenFWB17 fatcat:eibwd4tyjnh3xc76jafk32y5re

Toward systematic review automation: a practical guide to using machine learning tools in research synthesis

Iain J. Marshall, Byron C. Wallace
2019 Systematic Reviews  
Automation has been proposed or used to expedite most steps of the systematic review process, including search, screening, and data extraction.  ...  In this practical guide, we provide an overview of current machine learning methods that have been proposed to expedite evidence synthesis.  ...  involved, rather than being replaced Supervised learning: estimating model parameters using manually labelled data Distantly supervised: learning from pseudo, noisy 'labels' derived automatically by applying  ... 
doi:10.1186/s13643-019-1074-9 pmid:31296265 pmcid:PMC6621996 fatcat:qbhycs7mdvc5hjewzz3pv27yeq

Relation/Entity-Centric Reading Comprehension [article]

Takeshi Onishi
2020 arXiv   pre-print
More specifically, we focus on question answering tasks designed to measure reading comprehension.  ...  We focus on entities and relations because they are typically used to represent the semantics of natural language.  ...  Then, we describe reading comprehension datasets focusing on entities and relations, and also relation extraction from the point of view of reading comprehension.  ... 
arXiv:2008.11940v1 fatcat:ka44mwkforb4lfenw3odkosmem

Quasar: Datasets for Question Answering by Search and Reading [article]

Bhuwan Dhingra, Kathryn Mazaitis, William W. Cohen
2017 arXiv   pre-print
We also describe a retrieval system for extracting relevant sentences and documents from the corpus given a query, and include these in the release for researchers wishing to only focus on (2).  ...  We pose these datasets as a challenge for two related subtasks of factoid Question Answering: (1) searching for relevant pieces of text that include the correct answer to a query, and (2) reading the retrieved  ...  Acknowledgments This work was funded by NSF under grants CCF-1414030 and IIS-1250956 and by grants from Google.  ... 
arXiv:1707.03904v2 fatcat:5tf263qt7vfchmcmgbbge35weq

Neural Machine Reading Comprehension: Methods and Trends

Shanshan Liu, Xin Zhang, Sheng Zhang, Hui Wang, Weiming Zhang
2019 Applied Sciences  
Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques  ...  Although research on MRC based on deep learning is flourishing, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this  ...  -Noisy Document Retrieval Multi-passage MRC can be regarded as a distantly supervised open-domain question-answering task that may suffer from noise issues.  ... 
doi:10.3390/app9183698 fatcat:bpwwfikrpvh4dhphyl3ezpnn5e

First-principle study on honeycomb fluorated-InTe monolayer with large Rashba spin splitting and direct bandgap

Kaixuan Li, Xiujuan Xian, Jiafu Wang, Niannian Yu
2019 Applied Surface Science  
Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques  ...  Although research on MRC based on deep learning is flourishing, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this  ...  Conclusion This article presents a comprehensive survey on the progresses of neural machine reading comprehension.  ... 
doi:10.1016/j.apsusc.2018.11.214 fatcat:dg2eusl7ufhttcsqlllyiisxb4

Low-Resource Adaptation of Neural NLP Models [article]

Farhad Nooralahzadeh
2020 arXiv   pre-print
Real-world applications of natural language processing (NLP) are challenging. NLP models rely heavily on supervised machine learning and require large amounts of annotated data.  ...  The objective of this thesis is to investigate methods for dealing with such low-resource scenarios in information extraction and natural language understanding.  ...  "A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge". In: PSYCHOLOGICAL REVIEW vol. 104, no. 2, pp. 211-240.  ... 
arXiv:2011.04372v1 fatcat:626mbe5ba5bkdflv755o35u5pq
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