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Frontiers of Information Technology & Electronic Engineering

ISSN 2095-9184

Frontiers of Information Technology & Electronic Engineering  2017, Vol. 18 Issue (2): 195-205   https://doi.org/10.1631/FITEE.1500473
  本期目录
一种易用的实体识别消歧系统评测框架
辉 陈1(),宝刚 魏1(),一鸣 李1,Yong-huai LIU2,文浩 朱3
1. 浙江大学计算机科学与技术学院
2. Department of Computer Science, Aberystwyth University, Ceredigion SY23 3DB, UK
3. 上海大学计算机工程与科学学院
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Abstract

实体识别消歧是知识库扩充和信息抽取的重要技术之一。近些年该领域诞生了很多研究成果,提出了许多实体识别消歧系统。但由于缺乏对这些系统的完善评测对比,该领域依然处于良莠淆杂的状态。因此很有必要设计一个评测框架对各个系统进行统一评测。本文提出一个实体识别消歧系统的统一评测框架,用于公平地比较各个实体识别消歧系统的效果。该框架代码开源,可以采用新的系统、数据集、评测机制扩展。通过该框架评测实体系统,可以分析得到系统各个模块的优劣之处。本文分析对比了几个公开的实体识别消歧系统,并总结出了一些有用的结论。

Key words实体识别消歧    评测框架    信息抽取
收稿日期: 2015-12-26      出版日期: 2017-03-20
Corresponding Author(s): 辉 陈,宝刚 魏   
 引用本文:   
. [J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(2): 195-205.
辉 陈,宝刚 魏,一鸣 李,Yong-huai LIU,文浩 朱. 一种易用的实体识别消歧系统评测框架. Front. Inform. Technol. Electron. Eng, 2017, 18(2): 195-205.
 链接本文:  
https://academic.hep.com.cn/fitee/CN/10.1631/FITEE.1500473
https://academic.hep.com.cn/fitee/CN/Y2017/V18/I2/195
1 Bizer , C., Lehmann , J., Kobilarov , G., , 2009. DBpedia—a crystallization point for the Web of Data. Web Semant.Sci. Serv. Agents World Wide Web, 7(3):154–165.
2 Carletta , J., 1996. Assessing agreement on classification tasks: the kappa statistic.Comput. Ling., 22(2):249–254.
3 Cornolti , M., Ferragina , P., Ciaramita , M., 2013. A framework for benchmarking entity-annotation systems. Proc. 22nd Int. Conf. on World Wide Web, p.249–260.
4 Finkel , J.R., Grenager , T., Manning , C., 2005. Incorporating non-local information into information extraction systems by Gibbs sampling. Proc. 43rd Annual Meeting on Association for Computational Linguistics, p.363–370.
5 Hachey , B., Nothman , J., Radford , W., 2014. Cheap and easy entity evaluation. Proc. 52nd Annual Meeting of the Association for Computational Linguistics, p.464–469.
6 Hoffart , J., Yosef , M.A., Bordino , I., , 2011. Robust disambiguation of named entities in text. Proc. Conf. on Empirical Methods in Natural Language Processing, p.782–792.
7 Ji , H., Nothman , J., Hachey , B., , 2014. Overview of TAC-KBP2014 entity discovery and linking tasks. Proc. Text Analysis Conf.
8 Ji , H., Nothman , J., Hachey , B., , 2015. Overview of TAC-KBP2015 tri-lingual entity discovery and linking. Proc. Text Analysis Conf.
9 Ling , X., Singh , S., Weld , D.S., 2015. Design challenges for entity linking.Trans. Assoc. Comput. Ling., 3:315–328.
10 Milne , D., Witten , I.H., 2008. Learning to link with Wikipedia. Proc. 17th ACM Conf. on Information and Knowledge Management, p.509–518.
11 Milne , D., Witten , I.H., 2013. An open-source toolkit for mining Wikipedia.Artif. Intell., 194:222–239.
12 Ratinov , L., Roth , D., 2009. Design challenges and misconceptions in named entity recognition. Proc. 13th Conf. on Computational Natural Language Learning, p.147–155.
13 Ratinov , L., Roth , D., Downey , D., , 2011. Local and global algorithms for disambiguation to Wikipedia. Proc. 49th Annual Meeting of the Association for Computational Linguistics: Human Language, p.1375–1384.
14 Ristad , E.S., Yianilos , P.N., 1998. Learning string-edit distance.IEEE Trans. Patt. Anal. Mach. Intell., 20(5):522–532.
15 Rizzo , G., van Erp , M., Troncy , R., 2014. Benchmarking the extraction and disambiguation of named entities on the semantic web. Proc. 9th Int. Conf. on Language Resources and Evaluation.
16 Shen , W., Wang , J., Han , J., 2015. Entity linking with a knowledge base: issues, techniques, and solutions.IEEE Trans. Knowl. Data Eng., 27(2):443–460.
17 Spitkovsky , V.I., Chang , A.X., 2012. A cross-lingual dictionary for English Wikipedia concepts. 8th Int. Conf. on Language Resources and Evaluation, p.3168–3175.
18 Usbeck , R., Röder , M., Ngonga Ngomo , A.C., , 2015. GERBIL: general entity annotator benchmarking framework. Proc. 24th Int. Conf. on World Wide Web, p.1133–1143.
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