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Summarizing Entities using Distantly Supervised Information Extractors

Travis Wolfe, Annabelle Carrell, Mark Dredze, Benjamin Van Durme
2018 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval  
In particular we find that distantly supervised information extractors lead to significant improvements over lexical approaches, demonstrating the utility of extraction technologies for a task other than  ...  We describe entity summarization, the task of producing informative text summaries for an entity described across multiple documents in a collection.  ...  paths most frequent in positive distantly supervised examples.  ... 
dblp:conf/sigir/WolfeCDD18 fatcat:nntq7xyiyjepdac3pxz46bld34

Reducing Wrong Labels for Distantly Supervised Relation Extraction with Reinforcement Learning

Tiantian Chen, Nianbin Wang, Ming He, Liu Sun
2020 IEEE Access  
In this paper, the sentence-level label denoising model based on reinforcement learning (RL) and the express-only-one assumption is proposed for distantly supervised RE.  ...  Relation extraction (RE) aims to mine semantic relations between entity pairs from plain texts, which plays an important role in various natural language processing (NLP) tasks.  ...  SENTENCE ENCODING WITH PCNN PCNN aims to extract the word phase features and the structural information between two entities of each sentence, which is commonly used as a sentence encoder in distantly  ... 
doi:10.1109/access.2020.2990680 fatcat:ypwwa4dibzcvpiwp2mgm3lcgka

Stanford at TAC KBP 2016: Sealing Pipeline Leaks and Understanding Chinese

Yuhao Zhang, Arun Tejasvi Chaganty, Ashwin Paranjape, Danqi Chen, Jason Bolton, Peng Qi, Christopher D. Manning
2016 Text Analysis Conference  
This new system consists of several ruled-based relation extractors and a distantly supervised extractor.  ...  Our biggest contribution is an entirely new Chinese entity detection and relation extraction system for the new Chinese and cross-lingual relation extraction tracks.  ...  Acknowledgments The Stanford KBP 2016 team would like to acknowledge Gabor Angeli and Victor Zhong for their useful discussions about the 2016 system and great efforts in the development of Stanford's  ... 
dblp:conf/tac/ZhangCPCBQM16 fatcat:lp4pg2qn5fdnjbeewyzna6dlzq

Stanford at TAC KBP 2017: Building a Trilingual Relational Knowledge Graph

Arun Tejasvi Chaganty, Ashwin Paranjape, Jason Bolton, Matthew Lamm, Jinhao Lei, Abigail See, Kevin Clark, Yuhao Zhang, Peng Qi, Christopher D. Manning
2017 Text Analysis Conference  
This new Spanish system is a simple system that uses CRFbased entity recognition supplemented by gazettes followed by several ruled-based relation extractors, some using syntactic structure.  ...  We make further improvements to our systems for other languages, including improved named entity recognition, a new neural relation extractor, and better support for nested mentions and discussion forum  ...  Any opinions, findings, and conclusion or recommendations expressed in this material are those of the authors and do not necessarily reflect the view of the DARPA, AFRL, or the US government.  ... 
dblp:conf/tac/ChagantyPBLLSCZ17 fatcat:sfqef7ewv5fzhg7y2oowxeqny4

Combining Distant and Partial Supervision for Relation Extraction

Gabor Angeli, Julie Tibshirani, Jean Wu, Christopher D. Manning
2014 Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)  
We present an approach for providing partial supervision to a distantly supervised relation extractor using a small number of carefully selected examples.  ...  In this way, we combine the benefits of fine-grained supervision for difficult examples with the coverage of a large distantly supervised corpus.  ...  Any opinions, findings, and conclusion or recommendations expressed in this material are those of the authors and do not necessarily reflect the view of the DARPA, AFRL, or the US government.  ... 
doi:10.3115/v1/d14-1164 dblp:conf/emnlp/AngeliTWM14 fatcat:zv5l4dbahvhrxjp37uuh2gxeey

FarsBase-KBP: A Knowledge Base Population System for the Persian Knowledge Graph [article]

Majid Asgari-Bidhendi, Behrooz Janfada, Behrouz Minaei-Bidgoli
2020 arXiv   pre-print
The proposed system consists of a set of state-of-the-art modules such as an entity linking module as well as information and relation extraction modules designed for FarsBase.  ...  Then, the system uses knowledge fusion techniques with minimal intervention of human experts to integrate and filter the proper knowledge instances, extracted by each module.  ...  Six extractor components are used in total, including four information extractors and two relation extractors.  ... 
arXiv:2005.01879v1 fatcat:6dgj5ch6jbfd3kw7omblxblwfe

Knowledge base population using semantic label propagation

Lucas Sterckx, Thomas Demeester, Johannes Deleu, Chris Develder
2016 Knowledge-Based Systems  
Relation extraction (RE) is the task of assigning a semantic relationship between (pairs of) entities in text.  ...  Training relation extractors for the purpose of automated knowledge base population requires the availability of sufficient training data.  ...  We perform a highly selective form of noise reduction starting from a fully distantly supervised relation extractor, described in Section 3.1, and use the feature weights of this initial extractor to guide  ... 
doi:10.1016/j.knosys.2016.05.015 fatcat:woki5h75uffjdcevx436cufcoa

A Unified Model Using Distantly Supervised Data and Cross-Domain Data in NER

Yun Hu, Hao He, Zhengfei Chen, Qingmeng Zhu, Changwen Zheng, Shawkat ali
2022 Computational Intelligence and Neuroscience  
The distantly supervised data can provide in-domain dictionary information, and the hand-annotated cross-domain information can be provided by cross-domain data.  ...  These two types of information are complemental. However, there are two problems required to be solved before using directly. First, the distantly supervised data may contain a lot of noise.  ...  Feature Extractor. e feature extractor uses the output of word embedding.  ... 
doi:10.1155/2022/1987829 pmid:35676955 pmcid:PMC9168158 fatcat:zjyzk5vjife5jmsefsg2i5hmki

Knowledge Base Population using Semantic Label Propagation [article]

Lucas Sterckx and Thomas Demeester and Johannes Deleu and Chris Develder
2016 arXiv   pre-print
In this paper, we present a method that maximizes the effectiveness of newly trained relation extractors at a minimal annotation cost.  ...  A crucial aspect of a knowledge base population system that extracts new facts from text corpora, is the generation of training data for its relation extractors.  ...  We perform a highly selective form of noise reduction starting from a fully distantly supervised relation extractor, described in Section 3.1, and use the feature weights of this initial extractor to guide  ... 
arXiv:1511.06219v2 fatcat:jokbmhbxffexpa67jj4jbb6rdq

Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction [article]

Yujin Yuan, Liyuan Liu, Siliang Tang, Zhongfei Zhang, Yueting Zhuang, Shiliang Pu, Fei Wu, Xiang Ren
2018 arXiv   pre-print
Distant supervision leverages knowledge bases to automatically label instances, thus allowing us to train relation extractor without human annotations.  ...  In this paper, we propose to conduct multi-instance learning with a novel Cross-relation Cross-bag Selective Attention (C^2SA), which leads to noise-robust training for distant supervised relation extractor  ...  The final hyper-parameter setting used in our experiments are summarized in Table 2 .  ... 
arXiv:1812.10604v1 fatcat:drwtp6pajzcpflshn44yzdets4

Reinforcement Learning for Distantly Supervised Relation Extraction

Tingting Sun, Chunhong Zhang, Yang Ji, Zheng Hu
2019 IEEE Access  
The core of our label denoising is designing a policy in the PNet to obtain latent labels, where we can select the actions of using the distantly supervised labels or the predicted labels from the ENet  ...  In this paper, we propose a reinforcement learning-based label denoising method for distantly supervised relation extraction.  ...  from model prediction and distantly supervised information.  ... 
doi:10.1109/access.2019.2930340 fatcat:zyqmuznt6bh7leonfld7v7hq2a

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
It uses entity type and relation alias information for imposing soft constraints while predicting relations.  ...  Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically aligning relation instances in a Knowledge Base (KB) with unstructured text.  ...  Sentences in distance supervision are based on entities in KBs, where the type information is readily available.  ... 
arXiv:1812.04361v2 fatcat:xorwrvmu4jhmjn67dyedohfhxe

Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention [article]

Sharmistha Jat, Siddhesh Khandelwal, Partha Talukdar
2018 arXiv   pre-print
Distant Supervision (DS) is a popular technique for developing relation extractors starting with limited supervision.  ...  Firstly, we propose two novel word attention models for distantly- supervised relation extraction: (1) a Bi-directional Gated Recurrent Unit (Bi-GRU) based word attention model (BGWA), (2) an entity-centric  ...  Conclusion Distant Supervision (DS) has emerged as a promising approach to bootstrap relation extractors with limited supervision.  ... 
arXiv:1804.06987v1 fatcat:2to3s4gobzgjvmcrtl2jngesbm

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  
It uses entity type and relation alias information for imposing soft constraints while predicting relations.  ...  Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically aligning relation instances in a Knowledge Base (KB) with unstructured text.  ...  Sentences in distance supervision are based on entities in KBs, where the type information is readily available.  ... 
doi:10.18653/v1/d18-1157 dblp:conf/emnlp/VashishthJPBT18 fatcat:5fzlhteldzbedpoblowakpw2vy

Extreme Extraction: Only One Hour per Relation [article]

Raphael Hoffmann, Luke Zettlemoyer, Daniel S. Weld
2015 arXiv   pre-print
These extractors equal or outperform ones obtained by comparably supervised and state-of-the-art distantly supervised approaches.  ...  Information Extraction (IE) aims to automatically generate a large knowledge base from natural language text, but progress remains slow.  ...  This allows users to write rules which simultaneously use parse, coreference, and entity type information. (a) Rules.  ... 
arXiv:1506.06418v1 fatcat:b7h3yngagzfadhs5nqqaiult7q
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