A corpus-based finite-state morphological toolkit for contemporary Arabic

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10194805" target="_blank" >RIV/00216208:11320/13:10194805 - isvavai.cz</a>

Výsledek na webu

<a href="http://logcom.oxfordjournals.org/content/early/2013/01/08/logcom.exs070.abstract" target="_blank" >http://logcom.oxfordjournals.org/content/early/2013/01/08/logcom.exs070.abstract</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/logcom/exs070" target="_blank" >10.1093/logcom/exs070</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A corpus-based finite-state morphological toolkit for contemporary Arabic

Popis výsledku v původním jazyce

We develop an open-source large-scale ?nite-state morphological processing toolkit (AraComLex) for Modern StandardArabic (MSA) distributed under the GPLv3 license (http://aracomlex.sourceforge.net). The morphological transducer is based on a lexical database speci?cally constructed for this purpose. In contrast to previous resources, the database is tuned to MSA, eliminating lexical entries no longer attested in contemporary use. The database is built using a corpus of 1,089,111,204 word tokens, a pre-annotation tool, machine learning techniques and knowledge-based pattern matching to automatically acquire lexical knowledge. Our morphological transducer is evaluated and compared to LDC's SAMA(StandardArabic Morphological Analyser). We also develop a ?nite-state morphological guesser as part of a methodology for extracting unknown word forms, lemmatizing them, and giving them a priority weight for inclusion in the lexicon.

Název v anglickém jazyce

A corpus-based finite-state morphological toolkit for contemporary Arabic

Popis výsledku anglicky

We develop an open-source large-scale ?nite-state morphological processing toolkit (AraComLex) for Modern StandardArabic (MSA) distributed under the GPLv3 license (http://aracomlex.sourceforge.net). The morphological transducer is based on a lexical database speci?cally constructed for this purpose. In contrast to previous resources, the database is tuned to MSA, eliminating lexical entries no longer attested in contemporary use. The database is built using a corpus of 1,089,111,204 word tokens, a pre-annotation tool, machine learning techniques and knowledge-based pattern matching to automatically acquire lexical knowledge. Our morphological transducer is evaluated and compared to LDC's SAMA(StandardArabic Morphological Analyser). We also develop a ?nite-state morphological guesser as part of a methodology for extracting unknown word forms, lemmatizing them, and giving them a priority weight for inclusion in the lexicon.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AI - Jazykověda

OECD FORD obor

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Projekt

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Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Logic and Computation

ISSN

0955-792X

e-ISSN

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Svazek periodika

January 8,

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

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EID výsledku v databázi Scopus

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