1. Natural Language Generation Eric Clark CSC 9010-002

2. Natural Language Generation An essay on Natural Language Generation Are you sitting comfortably? I really, really like Natural Language Generation. Indispensable to homosapians today, it is yet to receive proper recognition for laying the foundations of democracy. It is estimated that that Natural Language Generation is thought about eight times every day by socialists, who form the last great hope for our civilzation. In the light of this I will break down the issues in order to give each of them the thought that they fully deserve.

3. NLG – Application Types Canned Text Template Filling Phrase Based Systems Feature Based Systems

4. Canned Text Download Complete “PC Load Letter”. What does that mean?

5. Template Filling Congratulations Eric. You have been pre-approved for a low 6.9 % interest rate on your new Citibank Gold Plus Titanium Super Mastercard.

6. Template Filling Mail Merge Smartform.com Aestiva

7. Phrase Based Systems Generalized Templates Phrase Pattern matched at top level [SUBJECT VERB OBJECT] [NP VP] [Det Adj Noun] Etc.

8. Phrase Based Systems Creates sentences effectively Limited to one sentence Scalability limited by interrelationships

9. Feature Based Systems Dictated by the characteristics of the sentence desired Positive/Negative Interrogative/Declarative Past/Present

10. Feature Based Systems Simplistic Language creation defined by the features New distinctions are just added to the list of other features

11. Cyc Created by Cycorp, Inc. Austin, TX “The Cyc Knowledge Server is a very large, multi-contextual knowledge base and inference engine”

12. Cyc Knowledge Base Inference Engine NL Processing Subsystem

13. Knowledge Base Facts Rules of Thumb Heuristics Terms Assertions

14. Inference Engine Logical Deduction Inference Mechanisms Best-first search

15. NL Processing Subsystem Lexicon Syntactic Parser Semantic Interpreter

16. NL Processing Subsystem Lexicon

17. NL Processing Subsystem Syntactic Parser {:SENTENCE {:NP {:DETP {#$Determiner [the]}} {:N-BAR {#$SimpleNoun [man]}}} {:VP {#$Verb [saw]} {:NP {:DETP {#$Determiner [the]}} {:N-BAR {#$SimpleNoun [light]}} {:PP {#$Preposition [with]} {:NP {:DETP {#$Determiner [the]}} {:N-BAR {#$SimpleNoun [telescope]}}}}}}}} The man saw the light with the telescope.

18. NL Processing Subsystem Semantic Interpreter “Mary believes that the blue hat is pretty“ (#$believes :SUBJECT :CLAUSE)

19. Research Cyc Based on OpenCyc Open Source Linux Based Has NLG capabilities Hybrid Phrase/Feature Based

20. Research Cyc “ResearchCyc is a version of the Cyc technology designed specifically for use by researchers”

21. The Problems with Meaningful Generation Limited to specific domains Not ready for Primetime Some useful “dumb” applications are still available

22. SCIGen Computer Science Research Paper Generator Computer Science Research Paper Generator “Our aim here is to maximize amusement, rather than coherence.” CSC 2180

23. Communications from Elsewhere Bad Poetry Band Names Post Modernism

24. Other Examples List of Work in NLG List

25. References Bateman, J. A. and Teich, E. (1995), `Selective information presentation in an integrated publication system: an application of genre-driven text generation', Information Processing and Management 31(5), 753-767. Bhattacharya, S, ‘Natural Language Generation’, accessed 2005 – available via Web: http://www.mla.iitkgp.ernet.in/~monojit/slides/NLG.ppt Uszkoreit, H ‘Language Generation’ accessed 2005 – available via Web: http://cslu.cse.ogi.edu/HLTsurvey/ch4node2.html http://cslu.cse.ogi.edu/HLTsurvey/ch4node2.html Natural language generation : third international conference, INLG 2004, Brockenhurst, UK, July 14-16, 2004 : proceedings / Anja Belz, Roger Evans, Paul Piwek (eds.) ResearchCyc – Cycorp Inc., accessed 2005 – available via Web: http://researchcyc.cyc.comhttp://researchcyc.cyc.com