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IPRE: a Dataset for Inter-Personal Relationship Extraction
[article]
2019
arXiv
pre-print
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Our data is the first dataset for inter-personal relationship extraction. ...
To address this situation, we introduce IPRE, a new dataset for inter-personal relationship extraction which aims to facilitate information extraction and knowledge graph construction research. ...
We would also thank the anonymous reviewers for their detailed comments, which have helped us to improve the quality of this work. ...
arXiv:1907.12801v2
fatcat:rutqlplcknbr3g4auvjdh4j46m
Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions
2019
Proceedings of the 2019 Conference of the North
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This paper presents a neural relation extraction method to deal with the noisy training data generated by distant supervision. ...
Here, each possible relation is utilized as the query for attention calculation instead of only using the target relation in conventional methods. ...
Acknowledgments We thank the anonymous reviewers for their valuable comments. ...
doi:10.18653/v1/n19-1288
dblp:conf/naacl/YeL19
fatcat:vzokpqv2gbhgroqy4uhliycuwq
Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions
[article]
2019
arXiv
pre-print
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This paper presents a neural relation extraction method to deal with the noisy training data generated by distant supervision. ...
Our method also achieves better relation extraction accuracy than state-of-the-art methods on this dataset. ...
Acknowledgments We thank the anonymous reviewers for their valuable comments. ...
arXiv:1904.00143v1
fatcat:44cuac67yvdp3bamxemg7sgxf4
Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
[article]
2018
arXiv
pre-print
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Secondly, we introduce GDS, a new distant supervision dataset for relation extraction. ...
We note that most of the sentences in the distant supervision relation extraction setting are very long and may benefit from word attention for better sentence representation. ...
We introduce GDS, a new distant supervision dataset for relation extraction. ...
arXiv:1804.06987v1
fatcat:2to3s4gobzgjvmcrtl2jngesbm
Chemical-induced disease relation extraction via attention-based distant supervision
2019
BMC Bioinformatics
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Results: We present an attention-based distant supervision paradigm for the BioCreative-V CDR extraction task. ...
Conclusion: Our experiments demonstrate that distant supervision is promising for extracting chemical disease relations from biomedical literature, and capturing both local and global attention features ...
Intra-sentence relation extraction In our attention-based distant supervision approach for intra-sentence relation extraction, a relation is considered as a bag B of multiple instances in different sentences ...
doi:10.1186/s12859-019-2884-4
fatcat:h2xnpdzlfffzrjqphubauszqp4
CANDiS: Coupled & Attention-Driven Neural Distant Supervision
[article]
2017
arXiv
pre-print
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Distant Supervision for Relation Extraction uses heuristically aligned text data with an existing knowledge base as training data. ...
We propose a novel technique, CANDiS, which casts distant supervision using inter-instance coupling into an end-to-end neural network model. ...
Distant Supervision (DS) for Relation Extraction was introduced by (Mintz et al., 2009 ) using a Freebase-aligned Wikipedia corpus. ...
arXiv:1710.09942v1
fatcat:pf4jzgxelrbmhoc4g3ozh4ynbm
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading Comprehension
[article]
2020
arXiv
pre-print
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Distant supervision (DS) is a promising approach for relation extraction but often suffers from the noisy label problem. ...
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. ...
Conclusion This paper proposes a new DS paradigm-the document-based distant supervision, which can effectively exploit all sentence-level, inter-sentencelevel, and entity-level evidence for relation extraction ...
arXiv:2012.04334v2
fatcat:4ab72nh2vfdrtddlrg5qienc2u
Distant Supervision for Relation Extraction beyond the Sentence Boundary
[article]
2017
arXiv
pre-print
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In this paper, we propose the first approach for applying distant supervision to cross- sentence relation extraction. ...
Experiments on an important extraction task for precision medicine show that our approach can learn an accurate cross-sentence extractor, using only a small existing knowledge base and unlabeled text from ...
Distant Supervision for Cross-Sentence Relation Extraction In this section, we present DISCREX, short for DIstant Supervision for Cross-sentence Relation EXraction. ...
arXiv:1609.04873v3
fatcat:6gwlyghskba6feufg2f3itqqqm
Crowdsourcing Ground Truth for Medical Relation Extraction
2018
ACM transactions on interactive intelligent systems (TiiS)
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2017 pre-print arXiv:1701.02185v1 fatcat:b6bwcev55zbuhks3n5nakrsrpeOther Versions
We report on using this method to build an annotated data set for medical relation extraction for the cause and treat relations, and how this data performed in a supervised training experiment. ...
data at scale than distant supervision. ...
Chang Wang for support with using the medical relation extraction classifier, and Anthony Levas for help with collecting the expert annotations. The authors, Dr. Wang and Mr. ...
doi:10.1145/3152889
fatcat:l3jtx2nur5ek3jtwqgbhxa67ky
Distant Supervision for Relation Extraction beyond the Sentence Boundary
2017
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
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In this paper, we propose the first approach for applying distant supervision to crosssentence relation extraction. ...
Experiments on an important extraction task for precision medicine show that our approach can learn an accurate cross-sentence extractor, using only a small existing knowledge base and unlabeled text from ...
Distant Supervision for Cross-Sentence Relation Extraction In this section, we present DISCREX, short for DIstant Supervision for Cross-sentence Relation EXraction. ...
doi:10.18653/v1/e17-1110
dblp:conf/eacl/QuirkP17
fatcat:m2gcbdzgdvfvblkmuldywhcmxe
CCKS 2019 Shared Task on Inter-Personal Relationship Extraction
[article]
2019
arXiv
pre-print
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The CCKS2019 shared task was devoted to inter-personal relationship extraction. ...
Given two person entities and at least one sentence containing these two entities, participating teams are asked to predict the relationship between the entities according to a given relation list. ...
We would like to thank all the contributors to Inter-Personal Relationship Extraction, including all participating teams and workers of data annotation, without their effort a task like this simply wouldn't ...
arXiv:1908.11337v1
fatcat:whqunvt4uvhlrnjrudq77lavpm
Denoising Relation Extraction from Document-level Distant Supervision
[article]
2020
arXiv
pre-print
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Distant supervision (DS) has been widely used to generate auto-labeled data for sentence-level relation extraction (RE), which improves RE performance. ...
To address this challenge, we propose a novel pre-trained model for DocRE, which denoises the document-level DS data via multiple pre-training tasks. ...
and Peng et al. (2017) attempt to extract inter-sentence relations with distantly supervised data. However, they only use entity pairs within three consecutive sentences. ...
arXiv:2011.03888v1
fatcat:xgl4tnngtvbipffaindsdg3nja
Learning Relation Ties with a Force-Directed Graph in Distant Supervised Relation Extraction
[article]
2020
arXiv
pre-print
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Relation ties, defined as the correlation and mutual exclusion between different relations, are critical for distant supervised relation extraction. ...
Furthermore, the proposed force-directed graph can be used as a module to augment existing relation extraction systems and improve their performance. ...
In distant supervised relation extraction, the purpose is to predict a set of target relations R (R ⊆ R) according to the entity pair (e 1 , e 2 ) and the sentence-bag S b . ...
arXiv:2004.10051v1
fatcat:xg7d3wikzvapnnct2gsfifksvm
DocRED: A Large-Scale Document-Level Relation Extraction Dataset
[article]
2019
arXiv
pre-print
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Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence ...
, and is the largest human-annotated dataset for document-level RE from plain text; (2) DocRED requires reading multiple sentences in a document to extract entities and infer their relations by synthesizing ...
Acknowledgement This work is supported by the National Key Research and Development Program of China (No. 2018YFB1004503), the National Natural Science Foundation of China (NSFC No. 61572273) and China Association for ...
arXiv:1906.06127v3
fatcat:tuc4znomjvdobl2fsakngxsv4q
Crowdsourcing Semantic Label Propagation in Relation Classification
[article]
2018
arXiv
pre-print
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Distant supervision is a popular method for performing relation extraction from text that is known to produce noisy labels. ...
Most progress in relation extraction and classification has been made with crowdsourced corrections to distant-supervised labels, and there is evidence that indicates still more would be better. ...
Introduction Distant supervision (DS) (Mintz et al., 2009 ) is a popular method for performing relation extraction from text. ...
arXiv:1809.00537v1
fatcat:4ekwr2mzgfgizippieafws35pe
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