@inproceedings{inui-etal-2006-augmenting,
title = "Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences",
author = "Inui, Kentaro and
Hirano, Toru and
Iida, Ryu and
Fujita, Atsushi and
Matsumoto, Yuji",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Gangemi, Aldo and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Tapias, Daniel",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/610_pdf.pdf",
abstract = "One of the crucial issues in semantic parsing is how to reduce costs of collecting a sufficiently large amount of labeled data. This paper presents a new approach to cost-saving annotation of example sentences with predicate-argument structure information, taking Japanese as a target language. In this scheme, a large collection of unlabeled examples are first clustered and selectively sampled, and for each sampled cluster, only one representative example is given a label by a human annotator. The advantages of this approach are empirically supported by the results of our preliminary experiments, where we use an existing similarity function and naive sampling strategy.",
}
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%0 Conference Proceedings
%T Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences
%A Inui, Kentaro
%A Hirano, Toru
%A Iida, Ryu
%A Fujita, Atsushi
%A Matsumoto, Yuji
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F inui-etal-2006-augmenting
%X One of the crucial issues in semantic parsing is how to reduce costs of collecting a sufficiently large amount of labeled data. This paper presents a new approach to cost-saving annotation of example sentences with predicate-argument structure information, taking Japanese as a target language. In this scheme, a large collection of unlabeled examples are first clustered and selectively sampled, and for each sampled cluster, only one representative example is given a label by a human annotator. The advantages of this approach are empirically supported by the results of our preliminary experiments, where we use an existing similarity function and naive sampling strategy.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/610_pdf.pdf
Markdown (Informal)
[Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences](http://www.lrec-conf.org/proceedings/lrec2006/pdf/610_pdf.pdf) (Inui et al., LREC 2006)
ACL