Building Discourse Parser for Thirukkural (2019)

Abstract: Thirukkural is one of the famous Tamil Literatures in the world. It was written by Thiruvalluvar, and focuses on ethics and morality. It provides all possible solutions to lead a successful and a peaceful life fitting any generation. It has been translated into 82 global languages, which necessitate the access of Thirukkural in any language on the World Wide Web (WWW) and processing the Thirukkural computationally. This paper aims at constructing the Thirukkural Discourse Parser which finds the semantic relations in the Thirukkurals which can extract the hidden meaning in it and help in utilizing the same in various Natural Language Processing (NLP) applications, such as, Summary Generation Systems, Information Retrieval (IR) Systems and Question Answering (QA) Systems. Rhetorical Structure Theory (RST) is one of the discourse theories, which is used in NLP to find the coherence between texts. This paper finds the relation within the Thriukkurals and the discourse structure is created using the Thirukkural Discourse Parser. The resultant discourse structure of Thirukkural can be indexed and further be used by Summary Generation Systems, IR Systems and QA Systems. This facilitates the end user to access Thirukkural on WWW and get benefited. This Thirukkural Discourse Parser has been tested with all 1330 Thirukurals using precision and recall.

## introduction tamil literature has so many nuggets hidden in it which need to be explored for the goodness of the society. one of the ways to explore the tamil literature is to make it easily accessible on the world wide web (www). for instance, thirukkural is one of the famous tamil literatures in the world and it is respected by people across the globe. in order to make it to reach to all people, it should be made available on the web. this makes necessary to process it computationally. hence, this paper proposes a methodology to perform a discourse analysis of thirukkural, which aids in exploring its semantics and also organizing it on the web. natural language processing (nlp) is the process of interaction between computer and human or natural languages. analysis of text can be done at various levels namely, word, clause, sentence, paragraph and document. discourse analysis is used for analyzing the text beyond the clause level. the proposed work attempts to extract the relations found within the thirukkural. discourse structure of a text can be built by using a popular theory called, rhetorical structure theory (rst) @xcite . using rstbased discourse relations, the rst captures the coherence among the natural language (nl) text spans. the coherence can be found between two or more text fragments. the text fragments could be within a sentence, across sentences, across paragraphs and even across documents. in this paper, each thirukkural is considered as a sentence and discourse parser is built using rst. the contributions of this paper are twofold. 1) finding feature set using rule based approach. 2) building discourse parser by identifying discourse relations. building discourse parser for thirukkural r. anita, c.n. subalalitha department of computer science and engineering srm institute of science and technology kattankulathur-603 203, tamilnadu, india {anitaramalingam17,subalalitha}@gmail.com the rest of the paper is organized as follows. section 2 describes background details. section 3 describes the related work. section 4 discusses the proposed work. section 5 gives details on the evaluation of the proposed technique. section 6 presents the conclusion and future works. ## background this section describes about the thirukkural and the basics of rst based discourse parsing. ## proposed work the tamil thirukkural couplets are given as input. initially the cue phrases or signal words are identified in each thirukkural. rst based discourse relations are identified by thirukkural discourse parser based on the cue words and semantics. then the nucleus and satellites are identified for each thirukkural. finally, the nrs sequences are identified as output from the thirukkural discourse parser. ## evaluation the features are extracted from 600 couplets. the 1330 thirukkural couplets are given as the input for the thirukkural discourse parser. the nrs sequences are identified by the thirukkural discourse parser based on the cue words. this work is evaluated using the parameters, precision and recall. precision (p), and recall (r) values are calculated using equations ( 1 ) and ( 2 (2) the in example 3 shown in figure 5 , two cue words "ஆற்றின் (arrin-if someone did)" and "பெறின் (perin-if received)" have appeared in the thirukkural. both cue words belong to the condition relation. in order to analyze the significance of each feature, the nrs sequences emerging out of two features present in the same thirukkural is counted and hence, m is greater than n. similarly, for evidence relation also m is greater than n. on the other side, in contrast, enablement and background relations, n is more than m. ## conclusion and future works thirukkural has much valuable information that is to be followed by the society. in order to access the thirukkural on the web, the semantic analysis of the same becomes necessary. this paper makes use of discourse theory, named, rst to do a discourse/semantic analysis on the thirukkural which will be useful to retrieve the thirukkural using an information retrieval system. keyword-based thirukkural search is available but limits the user to retreive the thirukkural containing only the query words. in this paper, we propose a methodology to construct a discourse parser for thirukkural which aids in semantic analysis and semantic representation of thirukkural. this kind of semantic representation can be used for efficient semantic indexing of thirukkural for better retrieval. using the results of the proposed discourse parser, an analysis of how thirukkural is written and organized is also evident which can be useful to write similar works in future. this kind of analysis can also help in automatic author detection of text @xcite . this paper focuses on the discourse relations present within a thirukkural couplet. it may be further extended to find the relations across the thirukkural couplets. an application that clearly depicts the discourse structure representation is also to be done.