Prague Arabic Dependency Treebank 1.0

registration: 2007/06/20 08:35:52, last modified: 2013/03/03 04:12:15
title
  • Prague Arabic Dependency Treebank 1.0
title.abbreviation
title.alternative
creator
  • Jan Hajic, Otakar Smrz, Petr Zemanek, Petr Pajas, Jan Snaidauf, Emanuel Beska, Jakub Kracmar, and Kamila Hassanova
subject
  • news databese
subject.linguisticField
  • computational_linguistics
  • syntax
  • morphology
subject.monoMultilingual
  • monolingual
subject.resourceSubject
  • corpus
description
  • Prague Arabic Dependency Treebank (PADT) not only consists of multi-level linguistic annotations over the language of Modern Standard Arabic, but even provides a variety of unique software implementations designed for general use in Natural Language Processing (NLP).
description.price *This metadata is only as a guide
  • non-member US$100.00
  • member US$100.00
description.language
  • English
description.inputDevice
description.inputEnvironment
description.speakingStyle
description.speechMode
description.samplingRate
description.additionalData
publisher
  • Linguistic Data Consortium(LDC)
contributor
contributor.attribute.author.motherTongue
contributor.attribute.author.dialect
contributor.attribute.author.level
contributor.attribute.author.age
contributor.attribute.author.gender
contributor.attribute.speaker.motherTongue
contributor.attribute.speaker.dialect
contributor.attribute.speaker.level
contributor.attribute.speaker.age
contributor.attribute.speaker.gender
contributor.attribute.speaker.number
date.created
date.issued
  • 2004-00-00
date.modified
type
  • Text
type.discourseType
  • report
type.linguisticType
  • primary_text
type.purpose
  • analysis cross-lingual information retrieval
  • analysis information retrieval
  • analysis language modeling
  • analysis machine translation
  • analysis natural language processing
  • analysis parsing
  • analysis tagging
type.style
  • written newswire
type.form
  • unfixed
type.sentence
  • short
  • long
type.annotation
  • annotated
type.annotationSample
type.sample
format.extent
  • over 113,500 tokens of data annotated analytically and provided with the disambiguated morphological information
  • more than 148,000 tokens, 49,000 of which have received the analytical processing
format.medium
  • 1CD
format.encoding
format.markup
format.functionality
  • cross-lingual information retrieval, information retrieval, language modeling, machine translation, natural language processing, parsing, tagging
identifier
identifier.doi
identifier.islrn
source
  • newswire
language
  • Arabic
language.area
  • Asia
relation
relation.utilization *This metadata is automatically extracted
  • Part-of-speech information and syntactic structure in the treebanks help with interpreting the distribution of information in the texts.
  • Over the past few years, treebanks have become important in various areas of computational linguistics ranging from syntactic to morphological and semantic-pragmatic applications.
  • With the rise of statistical methods in NLP, treebanks have become an important resource for various tasks: they are used to exemplify models of natural languages, to calculate probabilities of alternative generation rules, or to induce entire grammars.
  • The most widespread use of large treebanks is in developing and testing of automatic syntactic parsers, because both the training and the evaluation of a probabilistic parsing system require large amounts of annotated syntactic structures; but they are also useful as a source of examples for the creation of entirely rule-based NLP systems and other kinds of linguistic inquiry (Bouma and Kloosterman, 2002).
  • Finally, with large-scale treebanks available and static information of syntactic annotation derived from the treebanks, and with the help of large-scale thesaurus and machine learning techniques, we can explore the correspondence between linguistic forms, syntactic information and semantic information in the three different levels.
coverage.temporal
coverage.spacial
rights