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CS626-449: NLP, Speech and Web-Topics-in-AI

CS626-449: NLP, Speech and Web-Topics-in-AI. Pushpak Bhattacharyya CSE 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.

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CS626-449: NLP, Speech and Web-Topics-in-AI

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  1. CS626-449: NLP, Speech and Web-Topics-in-AI Pushpak BhattacharyyaCSE Dept., IIT Bombay Lecture 35: Semantic Relations; UNL; Towards Dependency Parsing

  2. Web at a glance • Google indexes more than 8 billion pages • Dominated by English • Large part of world is deprived of this knowledge

  3. Search Engines Today • Keyword based • Irrelevant results • Meaning not taken into account • Language specific • No search possible across language • No translation possible

  4. Future of the World Wide Web User User Translation interface Translation interface WWW User User

  5. Features • Meaning based • More relevant results • Multilingual • Query in English • Fetch document in Hindi • Show it in English

  6. Machine Translation • Translate from one language to other • Two approaches • Direct • One step • Using Intermediate language • Two step

  7. 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

  8. Internet for the Masses English interface Spanish interface Internet Spanishviewer English viewer Hindi interface Hindi viewer

  9. 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.

  10. UNL representation Representation of Knowledge Ram is reading the newspaper

  11. Knowledge Representation UNL Graph - relations read agt obj Ram newspaper

  12. Knowledge Representation UNL Graph - UWs read(icl>interpret) obj agt newspaper(icl>print_media) Ram(iof>person)

  13. 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

  14. 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

  15. UNL System

  16. The World-wide Universal Networking Language (UNL) Project Marathi • Language independent meaning representation. English Russian UNL Spanish Japanese Hindi

  17. The UNL System: An Overview

  18. Universal Networking Language • Universal Words (UWs) • Relations • Attributes • Knowledge Base

  19. 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.

  20. 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)

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