1. Indo WordNet A WordNet for Hindi
Debasri Chakrabarti, Dipak Kumar Narayan,
Prabhakar Pandey, Madhu Prasad Sharma
Centre for Technology Development for Indian Languages
Computer Science and Engineering Department, IIT Bombay

2. Introduction WordNet – A lexical database
Searching the dictionary conceptually
Different organizing principle for different syntactic category
Synsets or the Synonymy Sets are the basic building blocks
Lexical knowledge base is the heart of any intelligent information processing system

3. WordNet for Hindi
Hindi WordNet is an on-line lexical database for Hindi language
Design has been inspired by the famous English WordNet
Unique features
Graded antonyms and meronymy relationships
Efficient underlying database design
Cross part of speech linkage

4. Semantic relations in WordNet
Synonymy
Hypernymy / Hyponymy
Antonymy
Meronymy / Holonymy
Gradation
Entailment
Troponymy

5. Semantic Relations Synonymy {Gar ‚ kmara} {Gar ‚ Aavaasa}
True synonyms are rare
Synonymy related to a context
{Gar ‚ kmara}
{Gar ‚ Aavaasa}
{Gar ‚ janmakuMDlaIya sqaana}
{Gar ‚ svadoSa}

6. Semantic Relations Saor  pSau  sajaIva  Aist%va
Hypernymy and Hyponymy
Relation between word meaning (synsets)
X is a hyponym of Y if X is a kind of Y
Hyponymy is transitive and asymmetrical
Hypernymy is inverse of Hyponymy
lionanimalliving entityentity
Saor  pSau  sajaIva  Aist%va

7. Semantic Relations Antonymy Meronymy and Holonymy
Oppositeness in meaning
Relation between word forms
Meronymy and Holonymy
Part-whole relation, branch is a part of tree
X is a meronymy of Y if X is a part of Y
Meronym is transitive and asymmetrical
Holonymy is inverse relation of Meronymy

8. Troponym and Entailment
{ Kra-Ta laonaa – saaonaa £
Troponym
{ laÐgaD,anaa ‚ kdmatala krnaa – calanaa £
¡ fusafusaanaa – baaolanaa £

9. Antonymy Relation CaoTa – baD,a AcCa – baura rat – idna rama – ravaNa
Size
CaoTa – baD,a
Quality
AcCa – baura
State
rat – idna
Personality
rama – ravaNa
Direction
pUva- – piScama
Action
laonaa – donaa
Amount
kma – jyaada
Place
dUr – pasa
Time
saubah – Saama
Gender
baoTa – baoTI

10. Meronymy Relation maaqaa – SarIr p%qar – maUit- poD, – jaMgala
Component-object
maaqaa – SarIr
Stuff-object
p%qar – maUit-
Member-collection
poD, – jaMgala
Feature-Activity
BaaYaNa – samaaraoh
Place-Area
idllaI – Baart
Phase-State
javaanaI – ]ma`
Resource-process
klama – laoKna
Position-Area
icaik%sak – icaik%saa

11. Gradation bacapna ‚ javaanaI ‚ bauZ,apa baD,a ‚ maÐJalaa ‚ CaoTa
State
bacapna ‚ javaanaI ‚ bauZ,apa
Size
baD,a ‚ maÐJalaa ‚ CaoTa
Light
]jaalaa ‚ QauÐQalaa ‚ AÐQaora
Gender
mad- ‚ napuMsak ‚ AaOrt
Temperature
garma ‚ gaunagaunaa ‚ zMDa
Color
gaaora ‚ saaÐvalaa ‚ kalaa
Time
idna ‚ gaaoQaUila ‚ rat
Quality
AcCa ‚ saamaanya ‚ Kraba
Action
saaonaa ‚ }ÐGanaa ‚ jaaganaa
Manner
tojaI sao ‚ maQyama gait sao ‚ QaIro – QaIro

12. Classification of verbs
Simple verbs (sarla iËyaa) : saaonaa‚ Kanaa
Conjunct verbs iËyaa)
Compound verbs (samaaisak iËyaa) Á Kanaa–pInaa
Causative verbs (p`orNaa%mak iËyaa) Á saulavaanaa

13. WordNet Sub-Graph Gar , gaRh AQyana kxa Aavaasa , inavaasa Sayana kxa
Gloss
AQyana kxa
Hyponymy
Aavaasa , inavaasa
Sayana kxa
rsaao[-Gar
Gar , gaRh
manauYyaaoM ka Cayaa huAa vah sqaana jaao dIvaaraoM sao Gaor kr banaayaa jaata hO
Aitiqa gaRh
baramada
Aa^Mgana
AaEama
JaaopD,I
saMrcanaa
Meronymy M e r o n y m
Hypernymy

14. Design and Implementation
Basic relations or lexical links are between synonym sets
Lexical database is stored in MySQL package
Sub-tasks identified
Database design
Data entry interface
Implementation of Organizer Utility
Application programs to access and display the information in the lexical database

16. Data Entry Interface GUI designed in Java/JFC
Separate screen for data entry of different categories
Automatic generation of synset id’s
Screen to view the entered data

17. Synset Entry Interface

19. Organizer Utility Designed to preprocess the data
Reflexive pointers are generated
e.g. if A hypernym of B then B hyponym of A is automatically generated
Each semantic relation is mapped to a separate table (normalized)
Font conversion
Roman Hindi  DV-TTYogesh

20. Storage Structure Relation between Synsets Relation between Word-forms
tblNounHypernyms
Relation between Word-forms
tblNounAntonyms
Synset_Id
HyperSynset_Id
Synset_Id
Synset_Word
Anto_Id
Anto_Word
Anto_Type

24. System Statistics Over 8500 synsets entered in the database
MySQL used as the back-end database server
Data entry interface designed in Java/JFC
Organizer utility written in perl
Web based data retrieval system developed in HTML and PHP
DV-TTYogesh Font used to display Hindi Text

25. Application of WordNet
Word Sense Disambiguation
Interface to Internet Search Engines
Text classification
Information Retrieval system
Document Similarity

26. Conclusion
The structure of Hindi Language have been studied and new features have been introduced in the Hindi WordNet
Currently over 8500 synsets have been inserted into the database
The MySQL database has been found to be quite efficient
The web interface for querying the lexical database is under continuous evolution