@inproceedings{shamsfard-etal-2010-extracting,
title = "Extracting Lexico-conceptual Knowledge for Developing {P}ersian {W}ord{N}et",
author = "Shamsfard, Mehrnoush and
Fadaei, Hakimeh and
Fekri, Elham",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/784_Paper.pdf",
abstract = "Semantic lexicons and lexical ontologies are some major resources in natural language processing. Developing such resources are time consuming tasks for which some automatic methods are proposed. This paper describes some methods used in semi-automatic development of FarsNet; a lexical ontology for the Persian language. FarsNet includes the Persian WordNet with more than 10000 synsets of nouns, verbs and adjectives. In this paper we discuss extraction of lexico-conceptual relations such as synonymy, antonymy, hyperonymy, hyponymy, meronymy, holonymy and other lexical or conceptual relations between words and concepts (synsets) from Persian resources. Relations are extracted from different resources like web, corpora, Wikipedia, Wiktionary, dictionaries and WordNet. In the system presented in this paper a variety of approaches are applied in the task of relation extraction to extract ladled or unlabeled relations. They exploit the texts, structures, hyperlinks and statistics of web documents as well as the relations of English WordNet and entries of mono and bi-lingual dictionaries.",
}
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<abstract>Semantic lexicons and lexical ontologies are some major resources in natural language processing. Developing such resources are time consuming tasks for which some automatic methods are proposed. This paper describes some methods used in semi-automatic development of FarsNet; a lexical ontology for the Persian language. FarsNet includes the Persian WordNet with more than 10000 synsets of nouns, verbs and adjectives. In this paper we discuss extraction of lexico-conceptual relations such as synonymy, antonymy, hyperonymy, hyponymy, meronymy, holonymy and other lexical or conceptual relations between words and concepts (synsets) from Persian resources. Relations are extracted from different resources like web, corpora, Wikipedia, Wiktionary, dictionaries and WordNet. In the system presented in this paper a variety of approaches are applied in the task of relation extraction to extract ladled or unlabeled relations. They exploit the texts, structures, hyperlinks and statistics of web documents as well as the relations of English WordNet and entries of mono and bi-lingual dictionaries.</abstract>
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%0 Conference Proceedings
%T Extracting Lexico-conceptual Knowledge for Developing Persian WordNet
%A Shamsfard, Mehrnoush
%A Fadaei, Hakimeh
%A Fekri, Elham
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F shamsfard-etal-2010-extracting
%X Semantic lexicons and lexical ontologies are some major resources in natural language processing. Developing such resources are time consuming tasks for which some automatic methods are proposed. This paper describes some methods used in semi-automatic development of FarsNet; a lexical ontology for the Persian language. FarsNet includes the Persian WordNet with more than 10000 synsets of nouns, verbs and adjectives. In this paper we discuss extraction of lexico-conceptual relations such as synonymy, antonymy, hyperonymy, hyponymy, meronymy, holonymy and other lexical or conceptual relations between words and concepts (synsets) from Persian resources. Relations are extracted from different resources like web, corpora, Wikipedia, Wiktionary, dictionaries and WordNet. In the system presented in this paper a variety of approaches are applied in the task of relation extraction to extract ladled or unlabeled relations. They exploit the texts, structures, hyperlinks and statistics of web documents as well as the relations of English WordNet and entries of mono and bi-lingual dictionaries.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/784_Paper.pdf
Markdown (Informal)
[Extracting Lexico-conceptual Knowledge for Developing Persian WordNet](http://www.lrec-conf.org/proceedings/lrec2010/pdf/784_Paper.pdf) (Shamsfard et al., LREC 2010)
ACL