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Towards Entity Correctness, Completeness and Emergence for Entity Recognition

Authors:

Lei Zhang,

Yunpeng Dong,

Achim RettingerAuthors Info & Claims

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

Pages 143 - 144

https://doi.org/10.1145/2740908.2742766

Published: 18 May 2015 Publication History

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Abstract

Linking words or phrases in unstructured text to entities in knowledge bases is the problem of entity recognition and disambiguation. In this paper, we focus on the task of entity recognition in Web text to address the challenges of entity correctness, completeness and emergence that existing approaches mainly suffer from. Experimental results show that our approach significantly outperforms the state-of-the-art approaches in terms of precision, F-measure, micro-accuracy and macro-accuracy, while still preserving high recall.

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Cited By

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Liu MGong GQin BLiu T(2019)A Multi-View–Based Collective Entity Linking MethodACM Transactions on Information Systems10.1145/330019737:2(1-29)Online publication date: 6-Feb-2019
https://dl.acm.org/doi/10.1145/3300197
Varma SSameer NChowdary C(2019)ReLiC: entity profiling using random forest and trustworthiness of a sourceSādhanā10.1007/s12046-019-1178-x44:9Online publication date: 20-Aug-2019
https://doi.org/10.1007/s12046-019-1178-x
Petz GWetzlinger WNedbal D(2017)Improving Language-Dependent Named Entity DetectionMachine Learning and Knowledge Extraction10.1007/978-3-319-66808-6_22(330-345)Online publication date: 24-Aug-2017
https://doi.org/10.1007/978-3-319-66808-6_22
Show More Cited By

Index Terms

Towards Entity Correctness, Completeness and Emergence for Entity Recognition
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

1602 pages

ISBN:9781450334730

DOI:10.1145/2740908

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 May 2015

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the EU FP7 project XLiMe

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WWW '15

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IW3C2

WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Liu MGong GQin BLiu T(2019)A Multi-View–Based Collective Entity Linking MethodACM Transactions on Information Systems10.1145/330019737:2(1-29)Online publication date: 6-Feb-2019
https://dl.acm.org/doi/10.1145/3300197
Varma SSameer NChowdary C(2019)ReLiC: entity profiling using random forest and trustworthiness of a sourceSādhanā10.1007/s12046-019-1178-x44:9Online publication date: 20-Aug-2019
https://doi.org/10.1007/s12046-019-1178-x
Petz GWetzlinger WNedbal D(2017)Improving Language-Dependent Named Entity DetectionMachine Learning and Knowledge Extraction10.1007/978-3-319-66808-6_22(330-345)Online publication date: 24-Aug-2017
https://doi.org/10.1007/978-3-319-66808-6_22
Zhang LThalhammer ARettinger AFarber MMogadala ADenaux R(undefined)The Xlime System: Cross-Lingual and Cross-Modal Semantic Annotation, Search and Recommendation Over Live-Tv, News and Social Media StreamsSSRN Electronic Journal10.2139/ssrn.3199310
https://doi.org/10.2139/ssrn.3199310

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An optimization framework for entity recognition and disambiguation

First Steps in Czech Entity Linking

Named entity recognition an aid to improve multilingual entity filling in language-independent approach

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