Survey:Natural Language Parsing For Indian Languages
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paper_title: Computational Morphology and Natural Language Parsing for Indian Languages: A Literature Survey

paper_content:

Computational Morphology and Natural Language Parsing are the two important as well as essential tasks required for a number of natural language processing application including machine translation. Developing well fledged morphological analyzer and generator (MAG) tools or natural language parsers for highly agglutinative languages is a challenging task. The function of morphological analyzer is to return all the morphemes and their grammatical categories associated with a particular word form. For a given root word and grammatical information, morphological generator will generate the particular word form of that word. On the other hand Parsing is used to understand the syntax and semantics of a natural language sentences confined to the grammar. This literature survey is a ground work to understand the different morphology and parser developments in Indian language. In addition, the paper also deals with various approaches that are used to develop morphological analyzer and generator and natural language parsers tools.
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paper_title: Computational Morphology and Natural Language Parsing for Indian Languages: A Literature Survey

paper_content:

Computational Morphology and Natural Language Parsing are the two important as well as essential tasks required for a number of natural language processing application including machine translation. Developing well fledged morphological analyzer and generator (MAG) tools or natural language parsers for highly agglutinative languages is a challenging task. The function of morphological analyzer is to return all the morphemes and their grammatical categories associated with a particular word form. For a given root word and grammatical information, morphological generator will generate the particular word form of that word. On the other hand Parsing is used to understand the syntax and semantics of a natural language sentences confined to the grammar. This literature survey is a ground work to understand the different morphology and parser developments in Indian language. In addition, the paper also deals with various approaches that are used to develop morphological analyzer and generator and natural language parsers tools.
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paper_title: Parsing Free Word Order Languages In The Paninian Framework

paper_content:

There is a need to develop a suitable computational grammar formalism for free word order languages for two reasons: First, a suitably designed formalism is likely to be more efficient. Second, such a formalism is also likely to be linguistically more elegant and satisfying. In this paper, we describe such a formalism, called the Paninian framework, that has been successfully applied to Indian languages.This paper shows that the Paninian framework applied to modern Indian languages gives an elegant account of the relation between surface form (vibhakti) and semantic (karaka) roles. The mapping is elegant and compact. The same basic account also explains active-passives and complex sentences. This suggests that the solution is not just adhoc but has a deeper underlying unity.A constraint based parser is described for the framework. The constraints problem reduces to bipartite graph matching problem because of the nature of constraints. Efficient solutions are known for these problems.It is interesting to observe that such a parser (designed for free word order languages) compares well in asymptotic time complexity with the parser for context free grammars (CFGs) which are basically designed for positional languages.
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paper_title: Improving Data Driven Dependency Parsing using Clausal Information

paper_content:

The paper describes a data driven dependency parsing approach which uses clausal information of a sentence to improve the parser performance. The clausal information is added automatically during the parsing process. We demonstrate the experiments on Hindi, a language with relatively rich case marking system and free-word-order. All the experiments are done using a modified version of MSTParser. We did all the experiments on the ICON 2009 parsing contest data. We achieved an improvement of 0.87% and 0.77% in unlabeled attachment and labeled attachment accuracies respectively over the baseline parsing accuracies.
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paper_title: Simple Parser for Indian Languages in a Dependency Framework

paper_content:

This paper is an attempt to show that an intermediary level of analysis is an effective way for carrying out various NLP tasks for linguistically similar languages. We describe a process for developing a simple parser for doing such tasks. This parser uses a grammar driven approach to annotate dependency relations (both inter and intra chunk) at an intermediary level. Ease in identifying a particular dependency relation dictates the degree of analysis reached by the parser. To establish efficiency of the simple parser we show the improvement in its results over previous grammar driven dependency parsing approaches for Indian languages like Hindi. We also propose the possibility of usefulness of the simple parser for Indian languages that are similar in nature.
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paper_title: Dependency Parser for Bengali: the JU System at ICON 2009

paper_content:

This paper reports about our work in the ICON 2009 NLP TOOLS CONTEST: Parsing. We submitted two runs for Bengali. A statistical CRF based model followed by a rule-based post-processing technique has been used. The system has been trained on the NLP TOOLS CONTEST: ICON 2009 datasets. The system demonstrated an unlabeled attachment score (UAS) of 74.09%, labeled attachment score (LAS) of 53.90% and labeled accuracy score (LS) of 61.71% respectively.
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paper_title: Parsing of part-of-speech tagged Assamese Texts

paper_content:

A natural language (or ordinary language) is a language that is spoken, written, or signed by humans for general-purpose communication, as distinguished from formal languages (such as computer-programming languages or the"languages"used in the study of formal logic). The computational activities required for enabling a computer to carry out information processing using natural language is called natural language processing. We have taken Assamese language to check the grammars of the input sentence. Our aim is to produce a technique to check the grammatical structures of the sentences in Assamese text. We have made grammar rules by analyzing the structures of Assamese sentences. Our parsing program finds the grammatical errors, if any, in the Assamese sentence. If there is no error, the program will generate the parse tree for the Assamese sentence
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paper_title: Solving the Noun Phrase and Verb Phrase Agreement in Kannada Sentences

paper_content:

This paper proposes a way of producing context free grammar for solving Noun and Verb agreement in Kannada Sentences. In most of the Indian languages including Kannada a verb ends with a token which indicates the gender of the person (Noun/ Pronoun). This paper shows the implementation of this agreement using Context Free Grammar. It uses Recursive Descent Parser to parse the CFG. Around 200 sample sentences have taken to test the agreement.
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paper_title: Exploring Semantic Information in Hindi WordNet for Hindi Dependency Parsing

paper_content:

In this paper, we present our efforts towards incorporating external knowledge from Hindi WordNet to aid dependency parsing. We conduct parsing experiments on Hindi, an Indo-Aryan language, utilizing the information from concept ontologies available in Hindi WordNet to complement the morpho-syntactic information already available. The work is driven by the insight that concept ontologies capture a specific real world aspect of lexical items, which is quite distinct and unlikely to be deduced from morpho-syntactic information such as morph, POS-tag and chunk. This complementing information is encoded as an additional feature for data driven parsing and experiments are conducted. We perform experiments over datasets of different sizes. We achieve an improvement of 1.1% (LAS) when training on 1,000 sentences and 0.2% (LAS) on 13,371 sentences over the baseline. The improvements are statistically significant at p<0.01. The higher improvements on 1,000 sentences suggest that the semantic information could address the data sparsity problem.
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Title: Survey: Natural Language Parsing For Indian Languages

Section 1: INTRODUCTION
Description 1: Introduce the importance of syntactic parsing in natural language processing and highlight the challenges specifically faced in parsing Indian languages.

Section 2: BACKGROUNG THEORY
Description 2: Describe the different categories of natural language parsing techniques, including rule-based, statistical, and generalized parsing methods.

Section 3: LITERATURE SURVEY FOR INDIAN LANGUAGES
Description 3: Review the existing work on syntactic parsing for various Indian languages, detailing different parsers, methodologies, and results achieved.

Section 4: ISSUES IN SYNTACTIC PARSING
Description 4: Discuss the structural ambiguities and challenges faced in syntactic parsing of Indian languages, such as scope ambiguity and attachment ambiguity.

Section 5: PERFORMANCE MEASURES
Description 5: Explain the metrics used to evaluate the performance of syntactic parsers, such as precision, recall, and F-measure.

Section 6: CONCLUSION
Description 6: Summarize the survey, emphasizing the importance of annotated corpora for Indian languages and proposing future work towards creating efficient syntactic analyzers.