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Authors: Markus Schröder 1 ; 2 ; Christian Jilek 1 ; 2 ; Michael Schulze 1 ; 2 and Andreas Dengel 1 ; 2

Affiliations: 1 Computer Science Dept., TU Kaiserslautern, Germany ; 2 Smart Data & Knowledge Services Dept., DFKI GmbH, Kaiserslautern, Germany

Keyword(s): Person Index, Extraction, Short Text.

Abstract: When persons are mentioned in texts with their first name, last name and/or middle names, there can be a high variation which of their names are used, how their names are ordered and if their names are abbreviated. If multiple persons are mentioned consecutively in very different ways, especially short texts can be perceived as “messy”. Once ambiguous names occur, associations to persons may not be inferred correctly. Despite these eventualities, in this paper we ask how well an unsupervised algorithm can build a person index from short texts. We define a person index as a structured table that distinctly catalogs individuals by their names. First, we give a formal definition of the problem and describe a procedure to generate ground truth data for future evaluations. To give a first solution to this challenge, a baseline approach is implemented. By using our proposed evaluation strategy, we test the performance of the baseline and suggest further improvements. For future research th e source code is publicly available. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Schröder, M.; Jilek, C.; Schulze, M. and Dengel, A. (2021). The Person Index Challenge: Extraction of Persons from Messy, Short Texts. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 531-537. DOI: 10.5220/0010188405310537

@conference{icaart21,
author={Markus Schröder. and Christian Jilek. and Michael Schulze. and Andreas Dengel.},
title={The Person Index Challenge: Extraction of Persons from Messy, Short Texts},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={531-537},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010188405310537},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - The Person Index Challenge: Extraction of Persons from Messy, Short Texts
SN - 978-989-758-484-8
IS - 2184-433X
AU - Schröder, M.
AU - Jilek, C.
AU - Schulze, M.
AU - Dengel, A.
PY - 2021
SP - 531
EP - 537
DO - 10.5220/0010188405310537
PB - SciTePress