@inproceedings{shamsfard-2008-towards,
title = "Towards Semi Automatic Construction of a Lexical Ontology for {P}ersian",
author = "Shamsfard, Mehrnoush",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Tapias, Daniel",
booktitle = "Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)",
month = may,
year = "2008",
address = "Marrakech, Morocco",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2008/pdf/654_paper.pdf",
abstract = "Lexical ontologies and semantic lexicons are important resources in natural language processing. They are used in various tasks and applications, especially where semantic processing is evolved such as question answering, machine translation, text understanding, information retrieval and extraction, content management, text summarization, knowledge acquisition and semantic search engines. Although there are a number of semantic lexicons for English and some other languages, Persian lacks such a complete resource to be used in NLP works. In this paper we introduce an ongoing project on developing a lexical ontology for Persian called FarsNet. We exploited a hybrid semi-automatic approach to acquire lexical and conceptual knowledge from resources such as WordNet, bilingual dictionaries, mono-lingual corpora and morpho-syntactic and semantic templates. FarsNet is an ontology whose elements are lexicalized in Persian. It provides links between various types of words (cross POS relations) and also between words and their corresponding concepts in other ontologies (cross ontologies relations). FarsNet aggregates the power of WordNet on nouns, the power of FrameNet on verbs and the wide range of conceptual relations from ontology community.",
}
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<abstract>Lexical ontologies and semantic lexicons are important resources in natural language processing. They are used in various tasks and applications, especially where semantic processing is evolved such as question answering, machine translation, text understanding, information retrieval and extraction, content management, text summarization, knowledge acquisition and semantic search engines. Although there are a number of semantic lexicons for English and some other languages, Persian lacks such a complete resource to be used in NLP works. In this paper we introduce an ongoing project on developing a lexical ontology for Persian called FarsNet. We exploited a hybrid semi-automatic approach to acquire lexical and conceptual knowledge from resources such as WordNet, bilingual dictionaries, mono-lingual corpora and morpho-syntactic and semantic templates. FarsNet is an ontology whose elements are lexicalized in Persian. It provides links between various types of words (cross POS relations) and also between words and their corresponding concepts in other ontologies (cross ontologies relations). FarsNet aggregates the power of WordNet on nouns, the power of FrameNet on verbs and the wide range of conceptual relations from ontology community.</abstract>
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%0 Conference Proceedings
%T Towards Semi Automatic Construction of a Lexical Ontology for Persian
%A Shamsfard, Mehrnoush
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F shamsfard-2008-towards
%X Lexical ontologies and semantic lexicons are important resources in natural language processing. They are used in various tasks and applications, especially where semantic processing is evolved such as question answering, machine translation, text understanding, information retrieval and extraction, content management, text summarization, knowledge acquisition and semantic search engines. Although there are a number of semantic lexicons for English and some other languages, Persian lacks such a complete resource to be used in NLP works. In this paper we introduce an ongoing project on developing a lexical ontology for Persian called FarsNet. We exploited a hybrid semi-automatic approach to acquire lexical and conceptual knowledge from resources such as WordNet, bilingual dictionaries, mono-lingual corpora and morpho-syntactic and semantic templates. FarsNet is an ontology whose elements are lexicalized in Persian. It provides links between various types of words (cross POS relations) and also between words and their corresponding concepts in other ontologies (cross ontologies relations). FarsNet aggregates the power of WordNet on nouns, the power of FrameNet on verbs and the wide range of conceptual relations from ontology community.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/654_paper.pdf
Markdown (Informal)
[Towards Semi Automatic Construction of a Lexical Ontology for Persian](http://www.lrec-conf.org/proceedings/lrec2008/pdf/654_paper.pdf) (Shamsfard, LREC 2008)
ACL