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Contextual Entity Disambiguation in Domains with Weak Identity Criteria: Disambiguating Golden Age Amsterdamers

Authors:

Al Idrissou,

Veruska Zamborlini,

Frank Van Harmelen,

Chiara LatronicoAuthors Info & Claims

K-CAP '19: Proceedings of the 10th International Conference on Knowledge Capture

Pages 259 - 262

https://doi.org/10.1145/3360901.3364440

Published: 23 September 2019 Publication History

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Abstract

Entity disambiguation is a widely investigated topic, and many matching algorithms have been proposed. However, this task has not yet been satisfactorily addressed when the domain of interest provides poor or incomplete data with little discriminating power. In these cases, the use of content fields such as name and date is not enough and the simple use of relations with other entities is not of much help when these related entities also need disambiguation before they can be used. Therefore, we propose an approach for the disambiguation of clustered resources using context (related entities that are also clustered) as evidence for reconciling matched entities. We test the proposed method on datasets of historical records from Amsterdam in the 17th century for which context is available, and we compare the results of the proposed approach to a gold standard generated by three experts, which we make available online. The results show that the proposed approach manages to meaningfully use context for isolating identity sub-clusters with higher quality by eliminating potentially false positive matches.

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Cited By

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Idrissou AZamborlini VKuhn T(2022)Documenting the Creation, Manipulation and Evaluation of Links for Reuse and ReproducibilityKnowledge Engineering and Knowledge Management10.1007/978-3-031-17105-5_6(81-96)Online publication date: 26-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-17105-5_6

Index Terms

Contextual Entity Disambiguation in Domains with Weak Identity Criteria: Disambiguating Golden Age Amsterdamers
1. Applied computing
  1. Arts and humanities
2. Information systems
  1. Information systems applications
    1. Decision support systems

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Information & Contributors

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Published In

K-CAP '19: Proceedings of the 10th International Conference on Knowledge Capture

September 2019

281 pages

ISBN:9781450370080

DOI:10.1145/3360901

General Chairs:
Mayank Kejriwal
University of Southern California Information Sciences Institute, USA
,
Pedro Szekely
University of Southern California Information Sciences Institute, USA
,
Program Chair:
Raphaël Troncy
EURECOM, France

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 September 2019

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Short-paper

Funding Sources

NWO Large 2015-2016
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Conference

K-CAP '19

Sponsor:

SIGAI

K-CAP '19: Knowledge Capture Conference

November 19 - 21, 2019

CA, Marina Del Rey, USA

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Overall Acceptance Rate 55 of 198 submissions, 28%

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Idrissou AZamborlini VKuhn T(2022)Documenting the Creation, Manipulation and Evaluation of Links for Reuse and ReproducibilityKnowledge Engineering and Knowledge Management10.1007/978-3-031-17105-5_6(81-96)Online publication date: 26-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-17105-5_6

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Context Aware Named Entity Disambiguation

Entity Disambiguation with Linkless Knowledge Bases

DoSeR - A Knowledge-Base-Agnostic Framework for Entity Disambiguation Using Semantic Embeddings