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National Journal of Hindi & Sanskrit Research ~13~ ISSN: 2454-9177 NJHSR 2017; 1(12): 13-18 © 2017 NJHSR www.sanskritarticle.com Vivek Kumar Research Scholar Department of Sanskrit, Faculty of Arts University of Delhi, Delhi. Correspondence: Vivek Kumar Research Scholar Department of Sanskrit, Faculty of Arts University of Delhi, Delhi. Sanskrit Verb Form Generator Vivek Kumar Abstract In this era of information technology education in the field of very rapid growth. The role of e-learning is increasing in traditional education system. The purpose of this paper is to present a web-based system for Sanskrit verb form generator. By this medium anyone will be able to learn online Sanskrit Verb Form Generation Process with Sutras (Formula) everywhere. Sanskrit courses run by almost all Indian universities require Sanskrit Verb Formation Process. So this system will prove very useful. The system is being developed by consists of rules and examples base methods. Through which will receive the proper knowledge and Verb formation process regarding Paninian Bhvadigan Sanskrit verbs used in Sanskrit literature. The work is still under development. Keywords: Bhvadigan verbs, Verb Formation, Morphological Analyser, Sanskrit Morphology, kriyārūpasiddhi. Background There are about 2000 verbs in Sanskrit Language, from these verbs by adding tibādi eighteen suffixes 1 can made verb forms. Depending on their verb form structure, these verbs divided into ten categories 2 (gaṇa) (Chandra and Jha, 2011).These verbs can be three types- ātmanepadī, parasmaipadī and ubhayapadī (form are made in both parasmaipadī and ātmanepadī) (jhā, Ed., 2004). Some of these verbs may be aniand se3 .According to tense there are ten lakāra used in the Sanskrit language.There are some common features of Sanskrit verb forms in each lakāra (govindācārya, 2011 and śāstrī, 2004); for example śap 4 , guṇa 5 , antādeśa 6 etc. In la-lakāra verb forms are like calati, bhavati,paṭhanti etc.Inli-lakāra there are these works are common like doubling the verb (dvitva) 7 , work of abhyāsa, the affix ām 8 , ām ending verbs have annexed by kr̥ , bhū, as 9 like babhūva, edhāṁcakāra,edhāmbabhūva, edhāmāsa. In 1st Future (luṭ) the affix tās 10 , ḍā-rau-ras 11 substitutes, the augment i12 etc. are important; for example -paṭhitā, paṭhitārau, paṭhitāraḥ. In 2nd Future or Simple Future (lr̥ ṭ) the affix sya, augment i, gua etc. are fundamental works; like cariyati, bhaviyati, edhiyata. In lolakāra there are some primary works like śap, guṇa, ukāra 13 substitute instead of ikāra, the substitute tātaṅ 14 etc. For example - bhavatu, bhavatāt ādi (pāṇḍeya, 2004). At Imperfect or1st Preterite (lalakāra) the affixes aṭ or āṭ 15 or āṭ 16 , śap, guṇa, elision of ikāra, tāmādi 17 substitutes are major acts.Like abhavat, abhavatām, āṭat etc.In Potential (lilakāra) there are śap, yāsuṭ, sīyuṭ, gua, guaniedha etc.

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Page 1: ISSN: 2454 -9177 Sanskrit Verb Form Generator · National Journal of Hindi & Sanskrit ... same procedures for other languages such as English, Sanskrit ... Puranic Search: An Instant

National Journal of Hindi & Sanskrit Research

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ISSN: 2454-9177 NJHSR 2017; 1(12): 13-18 © 2017 NJHSR www.sanskritarticle.com

Vivek Kumar Research Scholar Department of Sanskrit, Faculty of Arts University of Delhi, Delhi.

Correspondence: Vivek Kumar Research Scholar Department of Sanskrit, Faculty of Arts University of Delhi, Delhi.

Sanskrit Verb Form Generator

Vivek Kumar

Abstract

In this era of information technology education in the field of very rapid growth. The role of e-learning is increasing in traditional education system. The purpose of this paper is to present a web-based system for Sanskrit verb form generator. By this medium anyone will be able to learn online Sanskrit Verb Form Generation Process with Sutras (Formula) everywhere. Sanskrit courses run by almost all Indian universities require Sanskrit Verb Formation Process. So this system will prove very useful. The system is being developed by consists of rules and examples base methods. Through which will receive the proper knowledge and Verb formation process regarding Paninian Bhvadigan Sanskrit verbs used in Sanskrit literature. The work is still under development.

Keywords: Bhvadigan verbs, Verb Formation, Morphological Analyser, Sanskrit Morphology, kriyārūpasiddhi.

Background

There are about 2000 verbs in Sanskrit Language, from these verbs by adding tibādi eighteen suffixes1 can made verb forms. Depending on their verb form structure, these verbs divided into ten categories2 (gaṇa) (Chandra and Jha, 2011).These verbs can be three types- ātmanepadī, parasmaipadī and ubhayapadī (form are made in both parasmaipadī and ātmanepadī) (jhā, Ed., 2004). Some of these verbs may be aniṭ and seṭ3.According to tense there are ten lakāra used in the Sanskrit language.There are some common features of Sanskrit verb forms in each lakāra (govindācārya, 2011 and śāstrī, 2004); for example śap4, guṇa5, antādeśa6 etc. In laṭ-lakāra verb forms are like calati, bhavati,paṭhanti etc.Inliṭ-lakāra there are these works are common like doubling the verb (dvitva)7 , work of abhyāsa, the affix ām8, ām ending verbs have annexed by kr̥, bhū, as9 like babhūva, edhāṁcakāra,edhāmbabhūva, edhāmāsa. In 1st Future (luṭ) the affix tās10, ḍā-rau-ras11substitutes, the augment iṭ12 etc. are important; for example -paṭhitā, paṭhitārau, paṭhitāraḥ. In 2nd Future or Simple Future (lr̥ṭ) the affix sya, augment iṭ, guṇa etc. are fundamental works; like cariṣyati, bhaviṣyati, edhiṣyata. In loṭ lakāra there are some primary works like śap, guṇa, ukāra13 substitute instead of ikāra, the substitute tātaṅ14 etc. For example - bhavatu, bhavatāt ādi (pāṇḍeya, 2004). At Imperfect or1st Preterite (laṅ lakāra) the affixes aṭ or āṭ15 or āṭ16 , śap, guṇa, elision of ikāra, tāmādi17 substitutes are major acts.Like abhavat, abhavatām, āṭat etc.In Potential (liṅ lakāra) there are śap, yāsuṭ, sīyuṭ, guṇa, guṇaniṣedha etc.

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functions following by Verbs important – bhavet, bhūyāt, edhiṣīṣṭa etc. (jijñāsu, 1998). Same as previous at 3 preterite or Aorist (lum̐ṅ) some of these common function are used to following by Verbs like sim̐c18 , elision of sim̐c19 , aṭ or āṭ; for example - abhaviṣyat, āṭiṣyat, abhaviṣyatām etc. (govindācārya, 2011 & śāstrī, 2004). It is known as per described above that most of the Verb Forms are same in lam̐ṭ; like - paṭhati, aṭati, namati, carati, edhate, spardhate, gādhate etc. On the contrary, there is a variation in the Verb forms of lim̐ṭ lakāra e.g. - babhūva, papāṭha, āta, edhāṁcakāra, paspardha, dedhe and more. often There are maximum equal verb forms of seṭ verbs in lum̐ṭ lakāra, but due to the rules of Juncture etc. are some differences in Verb form of aniṭ verbs such as seṭ verb forms like patitā, paṭhitā, aṭitā, caritā, hasitā and aniṭ Verb Forms such as kṣetā (kṣi), goptā (gup), jetā (ji), rantā (ram), smetā (smiṅ), gotā (guṅ) etc. Also in lr̥m̐ṭ should recognize same as lum̐ṭ such as seṭ Verbs - patiṣyati, paṭhiṣyati, aṭiṣyati, cariṣyati and aniṭ Verbs like - setsyati (sidh), gopsyati (gup), kṣeṣyati (kṣi), jeṣyati (ji) and more. Above procedure of Verb Forms is prescribed by Panini. Thus re-use of above process in this research will be done through the computer. For this Computer would be able to Recognize, Analyse and Formation.

Survey (Review)

In this age of information and communication technologies Jawaharlal Nehru University Distinguished Sanskrit name is foremost study centre for works of related to Sanskrit language. In the direction of DR. Girish Nath Jha many work has been done by the centre, which has several functions related to Tigant generator (Jha et.al), as well as other mechanisms Sanskrit texts such as the online index (Tiwari, 2011;), Subant Generator (Jha et. al) and Subant analyser (Jha et. al , 2006; Bhadra et. al, 2008; Jha et. al, 2009; Chandra, 2006; Chandra, 2011 & Chandra and Jha, 2011;), etc. are the main. The main objective of this centre is to translate Sanskrit to Indian Languages through Machine Translation. Similarly, all these mechanisms are part of this work In this area (University of Hyderabad http://sanskrit.uohyd.ernet.in/), Centre for Development of Advanced Computer (cdac.in), IIIT Hyderabad, Tirupati School, Central Language Institute, Mysore also have contributed and their contribution is also appreciable. Sanskrit Department of Delhi University is also began a work in the direction of Dr. Subhash Chandra in the area in the e-learning. There are an online learning tool called Swagatam ( वगतम्) has been developed for teaching and learning Sanskrit Grammar in Higher education. Swagatam is based on University of Delhi BA and MA Sanskrit syllabus. Swagatam is available at http://sanskrit.du.ac.in. Swagatam includes Taddhita (Sakshi & Chandra, 2015) and Sanadyanta Analyzer (Kumar & Chandra, 2016), Subanta Word formation System (Chandra et al, 2017a; Chandra et al, 2017b and Chandra et al, 2016), Sanskrit Meter Information System (Meena, 2015), Vedic Literature Search (Kumar, 2016), Pauranic Search System (Chandra & Singh, 2017) etc. Only One System is developed for Sanskrit Verbs Formation named Tigant Generator () which provide use Verb Formation Stage and Rule only like (vartamāne laṭ (3.2.123): 1 - bhū+lam̐ṭ( here Rule number also linked after clicking on it rule description in Sanskrit Language will be display in new tab. Verb is also linked with description of mādhavīyadhātuvr̥ttiḥ, kṣīrataraṅgiṇī, dhātupradīpaḥ, UoHyd, JNU, and INRIA. But after all of this the System is not fulfilling the eligibility of e-learning content. Thus our System is playing an important role in e-learning area also. Because of this anyone can learn easily without any book or reference. So requirement of this work is logistic. Sanskrit verb formation process is included in Sanskrit syllabus of almost all Indian universities. Any student as well as teacher can be learn and teach very easily by the help of this system.

Material and Methods

For computational analysis and formation of the verbs of bhvādigaṇa mainly on the basis of the rules laid down by Panini, computational rules will be built. So Panini rules related to the verbs of bhvādigaṇa used as a chief material. Normally, computational linguistics and software engineering is used to make system for recognition, analysis and Verb Formation of Sanskrit verbs related to bhvādigaṇa as well as Panini rule based and example based method. The following steps will be followed to create web-based system –

1.To make a Database to identify the verb forms of Suffixes of tiṅanta and lakāra based on siddhāntakaumudī.

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2.To create Database of pāṇini dhātupāṭha. 3.To develop a system to verbs recognition, analysis, and formation of verb forms related to bhvādigaṇa. Research methodology can be understood through Figure 1.

.

Figure 1: Research Methodology

Result & Discussions This system will have a user interface, which is shown in Figure 2. With the help of the user interface user can type in Unicode Devanagari verb form and by clicking on the button of the to get formation process, user can get complete formation process of input which is shown in Figure 3. In result all the rules will be hyperlinked, after moving the cursor on it shows meaning of particular rule & by clicking on them an explanation will be display in new tab. The meaning and interpretation of the sources are linked to the Rules, which means understanding the sources and proves to be very useful for teaching. Through the use of this system , any student in your studies and the teachers will be able to take easily to aid in teaching.

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National Journal of Hindi & Sanskrit Research

Figure 2: User Interface

This web-based system is fully based on the rules of aṣṭādhyāyī. Although the system is designed on the basis of the rule of aṣṭādhyāyī. Yet it was not possible on the basis of so many formations rule-based method has been used the example-based method for them. For example- `śr̥ṇoti’ form is singular and unique in itself, i.e., its similar process is not of any other form of function. Therefore, the example method will be used for this. Instead of many verbs, there are new verb orders in some lakāra, such as pib instead of pā in śit lakāra. In this situation also the example based method is under examination. some limitations of this system are following- 1. Formation process system is completely dependent on Recognition system. if Recognition would be so Analysis

could be wrong. 2. The formation of some verbs is similar as sidh (gatyām) & sidh (śāstre māṅgalye ca), añcu (gatipūjanayoḥ) & añcu

(gatiyācanayoḥ), kiṭa (bhaye) & kiṭa (gatau) etc. Which are difficult to analyse. Because it is difficult to identify the verb in such forms. For this both the possible formation process can be display..

Figure 3: User Interface

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Future Directions

The system is created to verbs of bhvādigaṇa. Based on this, other systems can be developed for other Ganas, which will be very important. As well as other Systems for kr̥danta, sanādyanta, samāsa, sandhi and taddhita can be developed. Yet this system is designed for students of Hindi mediums only later through the same procedures for other languages such as English, Sanskrit, Bengali, Tamil, Telugu, etc. can also be developed.

References:

1.tiptasjhisipthasthamibvasmastātāṁjhathāsāthāṁdhvamiḍvahimahiṅ । (aṣṭādhyāyī 3.4.78)

2.bhvādyadādī juhotyādirdivādiḥ svādireva ca / tudādiśca rudhādiśca tanakryādicurādayaḥ // (laghusiddhāntakaumudī, bhaimī vyākhyā, dvitīyabhāga, Page no -8 ). 3.dhātupāṭhaḥ (prastāvanā bhāga) . 4.kartari śap, aṣṭādhyāyī - 3.1.68 5.sārvadhātukārdhadhātukayoḥ, aṣṭādhyāyī - 7.3.84 6.jho'ntaḥ, aṣṭādhyāyī – 7.1.3 7.liṭi dhātoranabhyāsasya, aṣṭādhyāyī – 6.1.8 8.ijādeśca gurumato'nr̥cchaḥ, aṣṭādhyāyī – 3.1.36 9.kr̥ñ cānuprayujyate liṭi, aṣṭādhyāyī – 3.1.40 10.syatāsī lr̥luṭoḥ, aṣṭādhyāyī – 3.1.33 11.luṭaḥ prathamasya ḍāraurasaḥ, aṣṭādhyāyī – 2.4.85 12.ārdhadhātukasyeḍ valādeḥ, aṣṭādhyāyī – 7.2.35 13.eruḥ, aṣṭādhyāyī – 3.4.86 14.tuhyostātaṅāśiṣyanyatarasyām, aṣṭādhyāyī – 7.1.35 15.luṅlaṅlr̥ṅkṣvaḍudāttaḥ, aṣṭādhyāyī – 6.4.71 16.āḍajādīnām, aṣṭādhyāyī – 6.4.71 17.tasthasthamipāṁ tāntantāmaḥ,aṣṭādhyāyī - 3.4.101 18.cleḥ sic, aṣṭādhyāyī - 3.1.44 19.gātisthāghupābhūbhyaḥ sicaḥ parasmaipadeṣu, aṣṭādhyāyī - 2.4.77

Bibliography

1. Agrawal, Muktanand, 2007, Computational identification and analysis of Sanskrit verb-forms of bhvaadigana, M.Phil. Diss. Special Centre for Sanskrit Studies, Jawaharlal Nehru University, New Delhi.

2. Bhadra, Manji, Singh Surjit Kumar, Kumar Sachin, Chandra Subhash, Agrawal Muktanand, Chandrashekar R., Mishra Sudhir Kumar & Jha Girish Nath, 2009, Sanskrit Analysis System (SAS), Sanskrit Computational Linguistics Lecture Notes in Computer Science by Springer Berlin Heidelberg, Page 116-133.

3. Chandra Subhash, Kumar Bhupendra, Kumar Vivek and Sakshi, 2016, Lexical Resources for Detection, Analysis and Word Formation process for Sanskrit Morphology, In Proceedings of 3rd Workshop on Indian Language Data: Resources and Evaluation under 10th Edition of its Language Resources and Evaluation Conference (LREC-2015), Grand Hotel Bernardin Conference Center, Portorož (Slovenia) , pp.65-68.

4. Chandra, Subhash & Jha, Girish Nath, 2011, Computer Processing of Sanskrit Nominal Inflections: Methods and Implementation, Cambridge Scholars Publishing (CSP), 12Back Chapman Street, Newcastle upon Tyne.

5. Chandra, Subhash and Anju, 2017, Puranic Search: An Instant Search System for Puranas, Language in India, ISSN 1930-2940, Volume 17:5.

6. Chandra, Subhash, 2006, Machine Recognition and Morphological Analysis of Subanta-padas, Diss. Special Centre for Sanskrit Studies, Jawaharlal Nehru University, New Delhi.

7. Chandra, Subhash, Kumar, Bhupendra, Sakshi and Kumar, Vivek, 2017, laghusiddhāntakaumudī ādhārita kampyūṭarakr̥ta subanta-rūpa siddhi prakriyā, Vidyanidhi Prakashana, New Delhi, India.

8. Chandra, Subhash, Kumar, Vivek, Sakshi and Kumar Bhupendra, 2017, Innovative Teaching and Learning of Sanskrit Grammar through SWAGATAM . Language in India, ISSN 1930-2940, Volume 17:1.

9. govindācārya (Exp.) evaṁ śarmā, lakṣmī (Ed.), 2011, vaiyākaraṇasiddhāntakaumudī śrīdharamukhollāsinī hindī vyākhyā samanvitā, caukhambā surabhāratī prakāśana, vārāṇasī.

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10. Jha Girish Nath, Bhowmik Priti, Mishra Sudhir Kumar, Chandrashekar R, Chandra Subhash, Mendiratta Sachin & Agrawal

Muktanand, 2006, Towards a Computational analysis system for Sanskrit, Proceeding of first National symposium on Modeling and Shallow parsing of Indian Languages at Indian Institute of Technology Bombay, pp 25-34.

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Global Heritage: Scientific Perspectives (vedoṁ kī vaiśvika dharohara: vaijñānika āyāma), Special Centre for Sanskrit Studies, Jawaharlal Nehru University, New Delhi During, (Presented).

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14. Meena, Ravi Kumar, 2016, saṁskr̥ta chanda śikṣaṇa ke lie veba ādhārita sahāyaka taṁtra kā vikāsa, M.Phil. Diss., Special Centre for Sanskrit Studies, Jawaharlal Nehru University, New Delhi.

15. Patel, Dhaval & Katuri, Shiv kumari, 2016, Tinant Generator, Sanskritworld.in. 16. Sakshi and Chandra Subhash, 2015, niyama evaṁ udāharaṇa miśrita vidhi se vedānta granthoṁ ke vyākaraṇika viśleṣaṇa ke lie

taddhitānta padoṁ kī saṁgaṇakīya pahacāna evaṁ viśleṣaṇa, Twenty Second International Congress of Vedanta (22Vedanta), Special Centre for Sanskrit Studies, Jawaharlal Nehru University, New Delhi, (Presented).

17. śāstrī, bhīmasena, 2004, laghusiddhāntakaumudī, bhaimī prakāśana, Delhi. 18. Tiwari, Archana, 2011, Automatic Indexing of Carakasamhita, M.Phil. Diss., Special Centre for Sanskrit Studies, Jawaharlal

Nehru University, New Delhi.