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This lecture explores the importance of semantic relations in Natural Language Processing (NLP) and the challenges of current search engines, which often yield irrelevant results due to lack of meaning-based indexing. It introduces the Universal Networking Language (UNL) framework aimed at enabling multilingual semantic search. The talk also highlights two key approaches to machine translation: direct and interlingua-based, demonstrating how UNL serves as an intermediate language to enhance comprehension across diverse languages and improve accessibility to knowledge on the web.
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CS626-449: NLP, Speech and Web-Topics-in-AI Pushpak BhattacharyyaCSE Dept., IIT Bombay Lecture 35: Semantic Relations; UNL; Towards Dependency Parsing
Web at a glance • Google indexes more than 8 billion pages • Dominated by English • Large part of world is deprived of this knowledge
Search Engines Today • Keyword based • Irrelevant results • Meaning not taken into account • Language specific • No search possible across language • No translation possible
Future of the World Wide Web User User Translation interface Translation interface WWW User User
Features • Meaning based • More relevant results • Multilingual • Query in English • Fetch document in Hindi • Show it in English
Machine Translation • Translate from one language to other • Two approaches • Direct • One step • Using Intermediate language • Two step
Interlingua • Interlingua • Intermediate language for machine translation • Step one • Convert from source language text to interlingua • Step two • Produce target langauge text from interlingua • UNL : an interlingua in UNL system
Internet for the Masses English interface Spanish interface Internet Spanishviewer English viewer Hindi interface Hindi viewer
past tense bought time agent object student June computer the: definite in: modifier a: indefinite modifier new A Semantic Graph The student bought a new computer in June.
UNL representation Representation of Knowledge Ram is reading the newspaper
Knowledge Representation UNL Graph - relations read agt obj Ram newspaper
Knowledge Representation UNL Graph - UWs read(icl>interpret) obj agt newspaper(icl>print_media) Ram(iof>person)
Knowledge Representation UNL graph - attributes @entry @present @progress read(icl>interpret) obj agt @def newspaper(icl>print_media) Ram(iof>person) Ram is reading the newspaper
go(icl>move) @ entry @ past agt plt boy(icl>person) @ entry school(icl>institution) here agt plc :01 work(icl>do) The boy who works here went to school Another Example
The World-wide Universal Networking Language (UNL) Project Marathi • Language independent meaning representation. English Russian UNL Spanish Japanese Hindi
Universal Networking Language • Universal Words (UWs) • Relations • Attributes • Knowledge Base
forward(icl>send) @ entry @ past agt gol obj He(icl>person) minister(icl>person) @def mail(icl>collection) @def UNL Graph He forwarded the mail to the minister.
UNL Expression agt (forward(icl>send).@ entry @ past, he(icl>person)) obj (forward(icl>send).@ entry @ past, minister(icl>person)) gol (forward(icl>send ).@ entry @ past, mail(icl>collection). @def)