@inproceedings{tsvetkov-etal-2014-augmenting-english,
title = "Augmenting {E}nglish Adjective Senses with Supersenses",
author = "Tsvetkov, Yulia and
Schneider, Nathan and
Hovy, Dirk and
Bhatia, Archna and
Faruqui, Manaal and
Dyer, Chris",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/1096_Paper.pdf",
pages = "4359--4365",
abstract = "We develop a supersense taxonomy for adjectives, based on that of GermaNet, and apply it to English adjectives in WordNet using human annotation and supervised classification. Results show that accuracy for automatic adjective type classification is high, but synsets are considerably more difficult to classify, even for trained human annotators. We release the manually annotated data, the classifier, and the induced supersense labeling of 12,304 WordNet adjective synsets.",
}
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%0 Conference Proceedings
%T Augmenting English Adjective Senses with Supersenses
%A Tsvetkov, Yulia
%A Schneider, Nathan
%A Hovy, Dirk
%A Bhatia, Archna
%A Faruqui, Manaal
%A Dyer, Chris
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F tsvetkov-etal-2014-augmenting-english
%X We develop a supersense taxonomy for adjectives, based on that of GermaNet, and apply it to English adjectives in WordNet using human annotation and supervised classification. Results show that accuracy for automatic adjective type classification is high, but synsets are considerably more difficult to classify, even for trained human annotators. We release the manually annotated data, the classifier, and the induced supersense labeling of 12,304 WordNet adjective synsets.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/1096_Paper.pdf
%P 4359-4365
Markdown (Informal)
[Augmenting English Adjective Senses with Supersenses](http://www.lrec-conf.org/proceedings/lrec2014/pdf/1096_Paper.pdf) (Tsvetkov et al., LREC 2014)
ACL
- Yulia Tsvetkov, Nathan Schneider, Dirk Hovy, Archna Bhatia, Manaal Faruqui, and Chris Dyer. 2014. Augmenting English Adjective Senses with Supersenses. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 4359–4365, Reykjavik, Iceland. European Language Resources Association (ELRA).