Automatic Extraction of Part-whole Relations

Debela Tesfaye; Michael Zock

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Paper

Automatic Extraction of Part-whole Relations

In Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, 130-139, 2012 , Wrocław, Poland

Authors: Debela Tesfaye ¹ and Michael Zock ²

Affiliations: ¹ Addis Ababa University, Ethiopia ; ² CNRS and UMR 6166, France

ISBN: 978-989-8565-16-7

Keyword(s): part-whole relation extraction, semantic analysis, unsupervised meaning extraction

Abstract: The Web has become a universal repository of knowledge allowing to share information in a scale never seen before. Yet, with the growing size of the resource have grown the difficulties to access information. In this paper we present a system that automatically extracts Part-Whole relations among nouns. The approach is unsupervised, quasi language independent and does not require a huge resource like WordNet. The results show that the patterns used to extract Part-Whole relations can be learned from N-grams.

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Paper citation in several formats:

Tesfaye, D. and Zock, M. (2012). Automatic Extraction of Part-whole Relations.In Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2012) ISBN 978-989-8565-16-7, pages 130-139. DOI: 10.5220/0004113801300139

@conference{nlpcs12,
author={Debela Tesfaye. and Michael Zock.},
title={Automatic Extraction of Part-whole Relations},
booktitle={Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2012)},
year={2012},
pages={130-139},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004113801300139},
isbn={978-989-8565-16-7},
}

TY - CONF

JO - Proceedings of the 9th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2012)
TI - Automatic Extraction of Part-whole Relations
SN - 978-989-8565-16-7
AU - Tesfaye, D.
AU - Zock, M.
PY - 2012
SP - 130
EP - 139
DO - 10.5220/0004113801300139