TRIGRAMS’N’TAGS FOR LEXICAL KNOWLEDGE ACQUISITION

Berenike Litz, Hagen Langer, Rainer Malaka

Abstract

In this paper we propose a novel approach that combines syntactic and context information to identify lexical semantic relationships. We compiled semi-automatically and manually created training data and a test set for evaluation with the first sentences fromthe German version ofWikipedia. We trained the Trigrams’n’Tags Tagger by Brants (Brants, 2000) with a semantically enhanced tagset. The experiments showed that the cleanliness of the data is far more important than the amount of the same. Furthermore, it was shown that bootstrapping is a viable approach to ameliorate the results. Our approach outperformed the competitive lexico-syntactic patterns by 7% leading to an F1-measure of .91.

References

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Paper Citation


in Harvard Style

Litz B., Langer H. and Malaka R. (2009). TRIGRAMS’N’TAGS FOR LEXICAL KNOWLEDGE ACQUISITION . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009) ISBN 978-989-674-011-5, pages 18-25. DOI: 10.5220/0002292100180025


in Bibtex Style

@conference{kdir09,
author={Berenike Litz and Hagen Langer and Rainer Malaka},
title={TRIGRAMS’N’TAGS FOR LEXICAL KNOWLEDGE ACQUISITION},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)},
year={2009},
pages={18-25},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002292100180025},
isbn={978-989-674-011-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)
TI - TRIGRAMS’N’TAGS FOR LEXICAL KNOWLEDGE ACQUISITION
SN - 978-989-674-011-5
AU - Litz B.
AU - Langer H.
AU - Malaka R.
PY - 2009
SP - 18
EP - 25
DO - 10.5220/0002292100180025