A karaka based approach to parsing of Indian languages

Bharati, Agehananda; Sangal, Rajeev

doi:10.3115/991146.991151

Cited by 20 publications

(17 citation statements)

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“…Constraint based parsing using integer programming [36,18,37] has been successfully tested for Indian languages [38,39]. The parser uses the syntactic cues available in a sentence and forms constraint graphs (CG) on the basis of the generalizations available.…”

Section: Resultsmentioning

confidence: 99%

Development and Analysis of Verb Frame Lexicon for Hindi

Begum¹,

Sharma²

2017

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A verb frame (VF) captures various syntactic distributions where a verb can be expected to occur in a language. The argument structure of Hindi verbs (for various senses) is captured in the verb frames (VFs). The Hindi verbs were also classified based on their argument structure. The main objective of this work is to create a linguistic resource of Hindi verb frames which would: (i)Help the annotators in the annotation of the dependency relations for various verbs; (ii)Prove to be useful in parsing and for other Natural Language Processing (NLP) applications; (iii)Be helpful for scholars interested in the linguistic study of the Hindi verbs. In this study of Hindi verbs, the verb argument relations are captured using the dependency relations from Paninian Grammatical Framework (PGF). Analysis of Hindi verbs is the focus of this study since it gives us a good understanding of syntactic and semantic behaviour of verbs which is required for dependency annotation and for parsing. [1]. The preliminary work on this study was published as "Developing Verb Frames for Hindi" [1] in Language Resources and Evaluation Conference (LREC), 2008.

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Section: Resultsmentioning

confidence: 99%

Development and Analysis of Verb Frame Lexicon for Hindi

Begum¹,

Sharma²

2017

lls

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“…For example, in posting list of पर -D2:[ [2,1]] means in document D2 पर gives the relation between words present at positions 2 (टे बल) and 1 (ककताब) respectively (see figure 4). In documents D2 and D3, relation टे बल =>पर<= ककताब exists, that means ककताब is lying on the टे बल.…”

Section: ) Indexing a Spatial Relationmentioning

confidence: 99%

“…(see table I) [9] As Hindi is free order language; order of words contains only secondary information such as emphasis etc. Primary information relating to 'gross' meaning (e.g., one that includes semantic relationships) is contained elsewhere [1], [2], [3].…”

Section: A Case Role (Karaka) Relationmentioning

confidence: 99%

Relation Inclusive Search for Hindi Documents

Arora¹,

Vikas²

2013

IJACSA

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“…The first step in pre-processing comprises of removal of punctuation marks. Stop words are not removed, since Karaka theory is being used for generating phrases [2]. Karaka theory works only on complete sentences that necessarily includes stop words.…”

Section: Proposed Approach 31 Preprocessingmentioning

confidence: 99%

“…The semantic relations are captured by the Karaka Theory [2], which is a recently proposed semantic representation for sentences. The clustering method applied to the feature vectors is the hybrid of Vector Space Model and Frequent Sequence Concepts [3] [4].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Approach for Punjabi Text Clustering

Sharma¹,

Gupta²

2012

IJCA

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Text Clustering is a text mining technique which is used to group similar documents into single cluster by using some sort of similarity measure and placing dissimilar documents into different clusters. Most of the popular clustering algorithms treats document as conglomeration of words and do not consider the syntactic or semantic relations between words. To overcome this drawback, some algorithms were proposed which aimed at trying to find connections among different words in a sentence by using different concepts, e.g. Frequent Itemsets, Frequent Words Sequences, Frequent Word Meaning Sequences, Ontology based clustering. In this paper, we proposed a hybrid algorithm for clustering of Punjabi text document, which uses semantic relations among words in a sentence for extracting phrases. Phrases extracted create a feature vector of the document which is used for finding similarity among all documents. Results on experiment data reveal that hybrid algorithm is more reasonable and has a better performance with real time data sets.

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A karaka based approach to parsing of Indian languages

Cited by 20 publications

References 1 publication

Development and Analysis of Verb Frame Lexicon for Hindi

Development and Analysis of Verb Frame Lexicon for Hindi

Relation Inclusive Search for Hindi Documents

Hybrid Approach for Punjabi Text Clustering

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