REEL: A Relation Extraction Learning framework

机译：REEL：关系提取学习框架

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摘要

We introduce the REEL (RElation Extraction Learning) framework, an open source framework that facilitates the development and evaluation of relation extraction systems over text collections. To define a relation extraction system for a new relation and text collection, users only need to specify the parsers to load the collection, the relation and its constraints, and the learning and extraction techniques to be used. This makes REEL a powerful framework to enable the deployment and evaluation of relation extraction systems for both application building and research.

机译：我们介绍REEL（关系提取学习）框架，这是一个开放源代码框架，可帮助开发和评估基于文本集合的关系提取系统。要为新的关系和文本集合定义一个关系提取系统，用户只需指定解析器来加载集合，关系及其约束以及要使用的学习和提取技术。这使REEL成为一个强大的框架，可为应用程序构建和研究实现关系提取系统的部署和评估。

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来源
《2014 IEEE/ACM Joint Conference on Digital Libraries》|2014年|455-456|共2页
会议地点 London(GB)
作者
Barrio Pablo; Simoes Goncalo; Galhardas Helena; Gravano Luis;
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作者单位

Columbia University, USA;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Data mining; Feature extraction; Loading; Logic gates; Natural language processing; Text processing; Training;

机译：数据挖掘;特征提取;加载;逻辑门;自然语言处理;文本处理;培训;;

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专利

1. A neural network framework for relation extraction: Learning entity semantic and relation pattern [J] . Zheng Suncong, Xu Jiaming, Zhou Peng, Knowledge-Based Systems . 2016,第deca15期

机译：用于关系提取的神经网络框架：学习实体语义和关系模式
2. A Framework Using Active Learning to Rapidly Perform Named Entity Extraction and Relation Recognition for Science and Technology Knowledge Graph [J] . Ying Wang, Jing Dong, Peng Ren, Open Journal of Social Sciences . 2020,第9期

机译：使用主动学习的框架快速执行科技知识图表的命名实体提取和关系识别
3. Integrating shortest dependency path and sentence sequence into a deep learning framework for relation extraction in clinical text [J] . Zhiheng Li, Zhihao Yang, Chen Shen, BMC Medical Informatics and Decision Making . 2019,第1期

机译：将最短依赖路径和句子序列集成到深度学习框架中，以提取临床文本中的关系
4. REEL: A Relation Extraction Learning framework [C] . Barrio Pablo, Simoes Goncalo, Galhardas Helena, IEEE/ACM Joint Conference on Digital Libraries . 2014

机译：卷轴：关系提取学习框架
5. Learning for information extraction: From named entity recognition and disambiguation to relation extraction. [D] . Bunescu, Razvan Constantin. 2007

机译：学习信息提取：从命名实体识别和歧义消除到关系提取。
6. Integrating shortest dependency path and sentence sequence into a deep learning framework for relation extraction in clinical text [O] . Zhiheng Li, Zhihao Yang, Chen Shen, 2019

机译：将最短依赖路径和句子序列集成到深度学习框架中以提取临床文本中的关系
7. REEL: A Relation Extraction Learning Framework [O] . Pablo Barrio, Gonçalo Simões, Helena Galhardas, 2015

机译：REEL：关系提取学习框架

REEL: A Relation Extraction Learning framework

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