子句级别语境感知的开放信息抽取方法

doi:10.13229/j.cnki.jdxbgxb20170744

吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (5): 1563-1570.doi: 10.13229/j.cnki.jdxbgxb20170744

子句级别语境感知的开放信息抽取方法

欧阳丹彤^1,2, 范琪^1,2

1.吉林大学计算机科学与技术学院,长春130012;
2.吉林大学符号计算与知识工程教育部重点实验室,长春 130012

收稿日期:2017-07-13 出版日期:2018-09-20 发布日期:2018-12-11
作者简介:欧阳丹彤(1968-),女,教授,博士生导师.研究方向:基于模型诊断、语义网.E-mail:ouyd@jlu.edu.cn
基金资助:
国家自然科学基金项目(61672261,61502199,61402196,61373052);浙江省自然科学基金项目(LY16F020004)

Clause-level context-aware open information extraction

OUYANG Dan-tong^1,2, FAN Qi^1,2

1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
2.Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012, China

Received:2017-07-13 Online:2018-09-20 Published:2018-12-11

摘要/Abstract

摘要： 针对开放信息抽取文本中与事实相关的语境信息,本文首先从原有语境标识中提取特征进行训练分类,扩展了可识别的语境标识;其次,利用文本中依存关系,自顶向下逐层将识别出的语境信息与被限定子句构造成层次结构图,并最终根据层次图为被限定子句中抽取出的关系元组自底向上地分配对应语境域,从而一方面避免了语境信息被错误的抽取为关系元组,另一方面在保证关系元组正确的基础上,正确地将语境域分配给被限定的关系元组。实验结果验证了子句级别语境感知的抽取方法ClauseContextIE,在随机数据与含语境信息的文本中,实现了较高的召回率和精确度。

关键词: 计算机应用, 开放信息抽取, 语境感知, 子句级别, 依存解析

Abstract: In order to address the issue that sentences may contain context-information with reference to the facts, this paper presents a Clause-Level Context-aware Open Information Extraction approach (ClauseContextIE). ClauseContextIE extends the scale of context-information that can be identified, and takes advantage of the dependency-parsing to extract the context-information and general clauses in a top-down way, so that it can construct a graph that expresses the hierarchical structure. Finally, ClauseContextIE assigns the corresponding context-information to each tuple extracted from general clauses in a bottom-up approach. ClauseContextIE avoids extracting context-information as a relation tuple, and assigns context-information to correct relation tuples accurately. Experiments were conducted to compare ClauseContextIE with ReVerb, OLLIE and ClausIE on three datasets, ReVerb dataset, Wiki dataset and NYT dataset. Experimental results show that ClauseContextIE achieves significantly higher accuracy and recall than the other extractors.

Key words: computer application, open information extraction, context-aware, clause-level, dependency parsing

中图分类号:

TP391

欧阳丹彤, 范琪. 子句级别语境感知的开放信息抽取方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1563-1570.

OUYANG Dan-tong, FAN Qi. Clause-level context-aware open information extraction[J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1563-1570.

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子句级别语境感知的开放信息抽取方法

Clause-level context-aware open information extraction

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