@inproceedings{rouhizadeh-etal-2021-persian,
title = "{P}ersian {S}em{C}or: A Bag of Word Sense Annotated Corpus for the {P}ersian Language",
author = "Rouhizadeh, Hossein and
Shamsfard, Mehrnoush and
Dehghan, Mahdi and
Rouhizadeh, Masoud",
editor = "Vossen, Piek and
Fellbaum, Christiane",
booktitle = "Proceedings of the 11th Global Wordnet Conference",
month = jan,
year = "2021",
address = "University of South Africa (UNISA)",
publisher = "Global Wordnet Association",
url = "https://aclanthology.org/2021.gwc-1.17",
pages = "147--156",
abstract = "Supervised approaches usually achieve the best performance in the Word Sense Disambiguation problem. However, the unavailability of large sense annotated corpora for many low-resource languages make these approaches inapplicable for them in practice. In this paper, we mitigate this issue for the Persian language by proposing a fully automatic approach for obtaining Persian SemCor (PerSemCor), as a Persian Bag-of-Word (BoW) sense-annotated corpus. We evaluated PerSemCor both intrinsically and extrinsically and showed that it can be effectively used as training sets for Persian supervised WSD systems. To encourage future research on Persian Word Sense Disambiguation, we release the PerSemCor in \url{http://nlp.sbu.ac.ir}.",
}
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<abstract>Supervised approaches usually achieve the best performance in the Word Sense Disambiguation problem. However, the unavailability of large sense annotated corpora for many low-resource languages make these approaches inapplicable for them in practice. In this paper, we mitigate this issue for the Persian language by proposing a fully automatic approach for obtaining Persian SemCor (PerSemCor), as a Persian Bag-of-Word (BoW) sense-annotated corpus. We evaluated PerSemCor both intrinsically and extrinsically and showed that it can be effectively used as training sets for Persian supervised WSD systems. To encourage future research on Persian Word Sense Disambiguation, we release the PerSemCor in http://nlp.sbu.ac.ir.</abstract>
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%0 Conference Proceedings
%T Persian SemCor: A Bag of Word Sense Annotated Corpus for the Persian Language
%A Rouhizadeh, Hossein
%A Shamsfard, Mehrnoush
%A Dehghan, Mahdi
%A Rouhizadeh, Masoud
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 11th Global Wordnet Conference
%D 2021
%8 January
%I Global Wordnet Association
%C University of South Africa (UNISA)
%F rouhizadeh-etal-2021-persian
%X Supervised approaches usually achieve the best performance in the Word Sense Disambiguation problem. However, the unavailability of large sense annotated corpora for many low-resource languages make these approaches inapplicable for them in practice. In this paper, we mitigate this issue for the Persian language by proposing a fully automatic approach for obtaining Persian SemCor (PerSemCor), as a Persian Bag-of-Word (BoW) sense-annotated corpus. We evaluated PerSemCor both intrinsically and extrinsically and showed that it can be effectively used as training sets for Persian supervised WSD systems. To encourage future research on Persian Word Sense Disambiguation, we release the PerSemCor in http://nlp.sbu.ac.ir.
%U https://aclanthology.org/2021.gwc-1.17
%P 147-156
Markdown (Informal)
[Persian SemCor: A Bag of Word Sense Annotated Corpus for the Persian Language](https://aclanthology.org/2021.gwc-1.17) (Rouhizadeh et al., GWC 2021)
ACL