一、关系抽取(relation-extraction) 关系抽取就是从一段文本中抽取出(主体,关系,客体)这样的三元组,用英文表示就是(subject, relation, object)这样的三元组。所以关系抽取,有的论文也叫作三元组抽取。 从…
BERT(S) for Relation Extraction Overview A PyTorch implementation of the models for the paper"Matching the Blanks: Distributional Similarity for Relation Learning"published in ACL 2019. Note: This is not an official repo for the paper. Additional models for relation extraction, implemented here based...
1 论文动机 提出了一种基于Bert的模型,来进行关系抽取(Relation Extraction)和语义角色标注(Semantic Role Labeling) 不需要结合词汇和句法的特征,达到了SOTA的表现,为后续的研究提供了Baseline 2 模型介绍 2.1 关系抽取模型 关系抽取的模型示意图,如图所示: 输入句子的构成为: [[CLS] sentence [SEP] subject [SEP]...
BERT gated multi-window attention network for relation extraction 用于关系抽取的BERT门控多窗口注意力网络 Abstract 实体关系抽取旨在识别句子中实体对之间的语义关系,是问答系统、语义搜索等后续任务的重要技术支持。现有的关系抽取模型主要依靠神经网络来提取句子的语义信息,忽略了重要短语信息在关系抽取中的关键作用。
[1] Wu S , He Y . Enriching Pre-trained Language Model with Entity Information for Relation Classification[J]. 2019. [2] Giorgi J , Wang X , Sahar N , et al. End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models[J]. 2019. ...
incorporated.Our model also utilizes the intermediate layers of BERT to acquire different levels of semantic information and designs multi-granularity features for final relation classification.Our model offers a momentous improvement over the published methods for the relation extraction on the widely used...
今天给大家一篇关于生物医学关系提取方面的文章，“Improving BERT Model Using Contrastive Learning for BiomedicalRelation Extraction”。该文章的创新点在于引入了对比学习作为预训练步骤，将语言知识无缝集成到数据增强中，为关系提取任务量身定制。另外文章还研究了从外部知识库构建的大规模数据如何增强BERT对比预训练的...
[1] Wu S , He Y . Enriching Pre-trained Language Model with Entity Information for Relation Classification[J]. 2019. [2] Giorgi J , Wang X , Sahar N , et al. End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models[J]. 2019. ...
在transformer的情况下,这个分类器被添加到输出隐藏状态的顶部。有关关系提取的更多信息,请阅读这篇优秀的文章,其中概述了用于关系分类的微调transformer模型的理论:https://towardsdatascience.com/bert-s-for-relation-extraction-in-nlp-2c7c3ab487c4 我们将要微调的预训练模型是roberta基础模型,但是你可以使用...
Wu S , He Y . Enriching Pre-trained Language Model with Entity Information for Relation Classification[J]. 2019. 如上图所示,是R-BERT的模型结构在模型中,需要注意一下三点: 1.为了使BERT模型能够定位两个实体的位置,作者在每个句子的开头添加 "[CLS]" ,在第一个实体前后添加特殊字符 "$" ,在第二...