The Status of Case

Butt, Miriam; King, Tracy Holloway

doi:10.1007/978-1-4020-2719-2_6

Cited by 206 publications

(92 citation statements)

References 20 publications

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“…Urdu case markers are syntactic clitics (Butt and Sadler, 2003) and divided into different forms by Butt and King (2004) e.g., ergative, accusative, dative, possessive, etc. All Urdu case markers are annotated with a simple CM tag at POS level.…”

Section: Case Markersmentioning

confidence: 99%

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Semi-Semantic Annotation: A guideline for the URDU.KON-TB treebank POS annotation

Abbas

2016

ALA

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This work elaborates the semi-semantic part of speech annotation guidelines for the URDU.KON-TB treebank: an annotated corpus. A hierarchical annotation scheme was designed to label the part of speech and then applied on the corpus. This raw corpus was collected from the Urdu Wikipedia and the Jang newspaper and then annotated with the proposed semi-semantic part of speech labels. The corpus contains text of local & international news, social stories, sports, culture, finance, religion, traveling, etc. This exercise finally contributed a part of speech annotation to the URDU.KON-TB treebank. Twenty-two main part of speech categories are divided into subcategories, which conclude the morphological, and semantical information encoded in it. This article reports the annotation guidelines in major; however, it also briefs the development of the URDU.KON-TB treebank, which includes the raw corpus collection, designing & employment of annotation scheme and finally, its statistical evaluation and results. The guidelines presented will be useful for linguistic community to annotate sentences not only for the national language Urdu but for the other indigenous languages like Punjab, Sindhi, Pashto, etc. as well.Keywords: semi-semantic part of speech; rich information; deep learning; parsing aid; linguistically motivated annotation; humanistic annotation PovzetekRezultat tega dela so navodila za označevanje polsemantičnih besednih vrst v drevesnici URDU.KON-TB. Hierarhična označevalna shema je bila oblikovana z namenom, da razvrsti besedne vrste in jih kot take uporabi na korpusih. Tokratni koprus, ki je sestavljen iz strani Urdu Wikipedie in časopisa Jang, je bil označen s predlaganimi polsemantičnimi besednimi vrstami. Korpus vsebuje tekste lokalnih in mednarodnih novic, zgodbe s socialno temo, šport, kulturo, finance, vero, potovanja in druge teme. Uspešen poskusa označevanja je nadgradil drevesnico URDU.KON-TB. Dvaindvajset osnovnih besednih vrst je razdeljenih v podkategorije z morfološkimi in semantičnimi informacijami. Članek podaja jasne osnovne smernice označevanja. Hkrati ponuja kratek pregled razvoja drevesnice URDU.KON-TB, ki vsebuje zbirke surovih korpusov, oblikovanje in uporabo shem za označevanje ter nenazadnje tudi statistično oceno in rezultate. Predlagana navodila za označevanje so namenjena jezikovnim skupnostim, ki označujejo stavke tako v državnem jeziku Urdu kot tudi v drugih jezikih, kot so Punjab, Sindhi in drugih.Ključne besede: polsemantična besedna vrsta; številne informacije; globoko učenje; pomoč pri razvrščanju; jezikoslovno utemeljeno označevanje; humanistično označevanje 98 Qaiser ABBAS

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Section: Case Markersmentioning

confidence: 99%

“…The syntactic differentiation of the case markers is done according to the studies in Butt and King (2004).…”

Section: Employment Of Annotationmentioning

confidence: 99%

Semi-Semantic Annotation: A guideline for the URDU.KON-TB treebank POS annotation

Abbas

2016

ALA

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“…An abstract location can be identified through a spatial case marker (as discussed) and also through dative case marker. A dative case marker [9] can also be used to identify experiencer/SUB having some experience/PRD in a copular construction as given in example sentence 13. The respective c & f structures are depicted in figure 10.…”

Section: Attributive Copulamentioning

confidence: 99%

A Computational Classification of Dynamic Urdu Copula Verb

Abbas¹,

Raza²

2014

IJCA

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In this paper, a lexical functional grammar for an automatic classification of Urdu copula verb hO (be/become) is presented according to linguistic theories. A test suite of sentences containing almost all different conjugation forms of copula verb is extracted from a raw corpus. It is tried to keep only the cases of copular construction because the copula verb hO is very much dynamic in nature of function. The respective syntactic and functional structures of different cases of copular construction are presented, through which the lexical, syntactical and functional information required by copula verb is explored. The explorations made computationally are then compared with the existing linguistic theories as a proof of evaluation. It is an attempt to classify the state-of-the-art dynamic behavior of Urdu copula verb.

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“…However, these rules produce multiple categories for each word and hence multiple inflections which require · 15: 23 a separate model to perform disambiguation. The quality of these rules is superior as they are modeled based on the Urdu grammar analysis done by well known grammarians, Butt and King [2004] and Siddiqi [1971]. We used a variation of the work of Humayoun et al [2007] to develop our Urdu morphological analyzer.…”

Section: Morphological Analyzermentioning

confidence: 99%

An Information-Extraction System for Urdu---A Resource-Poor Language

Mukund

Srihari

Peterson³

2010

ACM Transactions on Asian Language Information Processing

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There has been an increase in the amount of multilingual text on the Internet due to the proliferation of news sources and blogs. The Urdu language, in particular, has experienced explosive growth on the Web. Text mining for information discovery, which includes tasks such as identifying topics, relationships and events, and sentiment analysis, requires sophisticated natural language processing (NLP). NLP systems begin with modules such as word segmentation, part-of-speech tagging, and morphological analysis and progress to modules such as shallow parsing and named entity tagging. While there have been considerable advances in developing such comprehensive NLP systems for English, the work for Urdu is still in its infancy. The tasks of interest in Urdu NLP includes analyzing data sources such as blogs and comments to news articles to provide insight into social and human behavior. All of this requires a robust NLP system. The objective of this work is to develop an NLP infrastructure for Urdu that is customizable and capable of providing basic analysis on which more advanced information extraction tools can be built. This system assimilates resources from various online sources to facilitate improved named entity tagging and Urdu-to-English transliteration. The annotated data required to train the learning models used here is acquired by standardizing the currently limited resources available for Urdu. Techniques such as bootstrap learning and resource sharing from a syntactically similar language, Hindi, are explored to augment the available annotated Urdu data. Each of the new Urdu text processing modules has been integrated into a general text-mining platform. The evaluations performed demonstrate that the accuracies have either met or exceeded the state of the art.

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The Status of Case

Cited by 206 publications

References 20 publications

Semi-Semantic Annotation: A guideline for the URDU.KON-TB treebank POS annotation

Semi-Semantic Annotation: A guideline for the URDU.KON-TB treebank POS annotation

A Computational Classification of Dynamic Urdu Copula Verb

An Information-Extraction System for Urdu---A Resource-Poor Language

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