Issues in Analyzing Telugu Sentences towards Building a Telugu Treebank

Vempaty, Chaitanya; Naidu, Viswanatha; Husain, Samar; V, Ravi Kiran; Bai, Lakshmi; Sharma, Dipti Misra; Sangal, Rajeev

doi:10.1007/978-3-642-12116-6_5

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…A few attempts were made in developing a Telugu dependency parser based on data-driven approaches. Some of them include Vempaty Chaitanya, Viswanatha Naidu, Samar Husain, Ravi Kiran, Lakshmi Bai, Dipti Mishra Sharma & Rajeev Sangal (2010) Rama, Taraka & Sowmya, Vajjala (2018) developed a Telugu treebank using Universal Dependency (UD) tagset with an addition of language-specific tags to handle compound and conjunct verb phrases for Telugu. Gatla (2019) developed a treebank for Telugu which was trained using data-driven parsers, namely, Minimum-Spanning Tree (MST) parser and Models and Algorithms for Language Technology (MALT) parser.…”

Section: Brief Surveymentioning

confidence: 99%

A Rule-based Dependency Parser for Telugu: An Experiment with Simple Sentences

Sangeetha¹,

Parameswari²,

Kulkarni³

2021

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This paper is an attempt in building a rule-based dependency parser for Telugu which can parse simple sentences. This study adopts Pāṇini’s Grammatical (PG) tradition i.e., the dependency model to parse sentences. A detailed description of mapping semantic relations to vibhaktis (case suffixes and postpositions) in Telugu using PG is presented. The paper describes the algorithm and the linguistic knowledge employed while developing the parser. The research further provides results, which suggest that enriching the current parser with linguistic inputs can increase the accuracy and tackle ambiguity better than existing data-driven methods.

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Section: Brief Surveymentioning

confidence: 99%

A Rule-based Dependency Parser for Telugu: An Experiment with Simple Sentences

Sangeetha¹,

Parameswari²,

Kulkarni³

2021

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“…inian Grammar (CPG), a brief introduction to which is given in the next section. Vempaty et al [14] give a detailed account of the issues encountered in the application of this annotation scheme to the treebanking of Telugu along with the decisions taken to address each of them in the development of version 0.1 of the treebank. They also discuss a few syntactic constructions in Telugu which are of interest from the parsing perspective.…”

Section: Related Work and Backgroundmentioning

confidence: 99%

External Sandhi and its Relevance to Syntactic Treebanking

Kolachina¹,

Sharma²,

Gadde³

et al. 2011

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External sandhi is a linguistic phenomenon which refers to a set of sound changes that occur at word boundaries. These changes are similar to phonological processes such as assimilation and fusion when they apply at the level of prosody, such as in connected speech. External sandhi formation can be orthographically reflected in some languages. External sandhi formation in such languages, causes the occurrence of forms which are morphologically unanalyzable, thus posing a problem for all kind of NLP applications. In this paper, we discuss the implications that this phenomenon has for the syntactic annotation of sentences in Telugu, an Indian language with agglutinative morphology. We describe in detail, how external sandhi formation in Telugu, if not handled prior to dependency annotation, leads either to loss or misrepresentation of syntactic information in the treebank. This phenomenon, we argue, necessitates the introduction of a sandhi splitting stage in the generic annotation pipeline currently being followed for the treebanking of Indian languages. We identify one type of external sandhi widely occurring in the previous version of the Telugu treebank (version 0.2) and manually split all its instances leading to the development of a new version 0.5. We also conduct an experiment with a statistical parser to empirically verify the usefulness of the changes made to the treebank. Comparing the parsing accuracies obtained on versions 0.2 and 0.5 of the treebank, we observe that splitting even just one type of external sandhi leads to an increase in the overall parsing accuracies.

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“…Various techniques are employed for parsing in different natural languages like statistical dependency, graph based, transition based etc [9][10][11][12][13][14][15]. In this paper, we describe such a formalism, called the Paninian framework, that has been successfully applied to hindi language and the same is applicable to the nepali language also.…”

Section: Introductionmentioning

confidence: 99%

Parsing Techniques using Paninian Framework on Nepali Language

Yajnik¹,

Sharma²

2015

DJ JEAM

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This paper presents three parsing techniques for establishing karaka-vibhakti relations using Paninian framework for nepali language. It uses the concept of karaka relation between verbs and nouns in the sentence. The constraints problem reduces to bipartite graph matching problem because of the nature of constraints and bipartite graph reduces to hopfield network. Upon employing these three techniques viz. constraint based , bipartite graph matching problem and hopfield networks using the Paninial framework to the sentences of nepali language an elegant account of the relation between surface form (vibhakti) and semantic (karaka) roles is obtained. All the three techniques are demonstrated by forming parsing structure in various nepali sentences.

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Issues in Analyzing Telugu Sentences towards Building a Telugu Treebank

Cited by 7 publications

References 5 publications

A Rule-based Dependency Parser for Telugu: An Experiment with Simple Sentences

A Rule-based Dependency Parser for Telugu: An Experiment with Simple Sentences

External Sandhi and its Relevance to Syntactic Treebanking

Parsing Techniques using Paninian Framework on Nepali Language

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