1. Natural Language Generation
Language Technology
Meaning
Natural Language Understanding
Natural Language Generation
Text
Text
Speech Recognition
Speech Synthesis
Speech
Speech

2. Natural Language Generation
Language Technology
Meaning
Natural Language Understanding
Natural Language Generation
Text
Text
Speech Recognition
Speech Synthesis
Speech
Speech

3. What is NLG?
Natural language generation is the process of deliberately constructing a natural language text in order to meet specified communicative goals.
[McDonald 1992]

4. Example System: FoG Function: Input: User: Developer: Status:
Produces textual weather reports in English and French
Input:
Graphical/numerical weather depiction
User:
Environment Canada (Canadian Weather Service)
Developer:
CoGenTex
Status:
Fielded, in operational use since 1992

5. FoG: Input

6. FoG: Output

7. Example System: TEMSIS
Function:
Summarises pollutant information for environmental officials
Input:
Environmental data + a specific query
User:
Regional environmental agencies in France and Germany
Developer:
DFKI GmbH
Status:
Prototype developed; requirements for fielded system being analysed

8.
TEMSIS

9. TEMSIS: Output Summary
Le 21/7/1998 à la station de mesure de Völklingen -City, la valeur moyenne maximale d'une demi-heure (Halbstundenmittelwert) pour l'ozone atteignait µg/m³. Par conséquent, selon le decret MIK (MIK-Verordnung), la valeur limite autorisée de 120 µg/m³ n'a pas été dépassée.
Der höchste Halbstundenmittelwert für Ozon an der Meßstation Völklingen -City erreichte am µg/m³, womit der gesetzlich zulässige Grenzwert nach MIK-Verordnung von 120 µg/m³ nicht überschritten wurde.

10. A further system ILEX SUMTIME
generation of virtual museum information online
SUMTIME
generation of weather reports

11. TEMSIS: Input Query
((LANGUAGE FRENCH) (GRENZWERTLAND GERMANY) (BESTAETIGE-MS T)
(BESTAETIGE-SS T)
(MESSSTATION \"Voelklingen City\")
(DB-ID \"#2083\")
(SCHADSTOFF \"#19\")
(ART MAXIMUM)
(ZEIT ((JAHR 1998)
(MONAT 7)
(TAG 21))))

12. Basic Generation Problem
How to go from an abstract semantic input to a concrete linguistic form that is
semantically correct
stylistically appropriate
textually appropriate
???

13. Standard Pipelined Architecture
Document Planning
Document Plan
Microplanning
Text Specification
Surface Realisation

14. KPML TACTICAL GENERATOR semantics lexicogrammar Semantic specification
sentence

15. KPML TACTICAL GENERATOR semantics lexicogrammar KPML is a Process
generation
engine
Semantic specification
Resources
KPML
semantics
lexicogrammar
sentence

16. TACTICAL GENERATION semantics lexicogrammar Semantic specification
sentence

17. What is NLG? NLG is a process of choice under specified constraints
Natural language generation is the process of deliberately constructing a natural language text in order to meet specified communicative goals.
NLG is a process of choice under specified constraints
[McDonald]

18. Linguistic Description with system networks
imperative
interrogative
Finite^Subject
indicative
+Finite
AXES
declarative
syntagmatic
Subject^Finite
paradigmatic

19. Resource Architecture in KPML:
system networks
imperative
indicative
interrogative
declarative
lexicogrammar

20. Resource Architecture in KPML:
system networks
grammatical
systems
imperative
interrogative
indicative
declarative

21. Resource Architecture in KPML:
system networks
grammatical
features
imperative
interrogative
indicative
declarative

22. Resource Architecture in KPML:
system networks
imperative
interrogative
Finite^Subject
indicative
+Finite
declarative
Subject^Finite

23. Resource Architecture in KPML:
system networks
realization
statements
imperative
interrogative
Finite^Subject
indicative
+Finite
declarative
Subject^Finite

24. Generation Process: system networks imperative interrogative
Finite^Subject
indicative
+Finite
declarative
Subject^Finite

25. Generation Process: system networks imperative interrogative
Finite^Subject
indicative
+Finite
declarative
Subject^Finite

26. Generation Process: traversal imperative interrogative Finite^Subject
indicative
+Finite
declarative
Subject^Finite

27. Generation Process: traversal imperative interrogative Finite^Subject
indicative
+Finite
declarative
Subject^Finite

28. Generation Process: traversal imperative interrogative Finite^Subject
indicative
+Finite
declarative
Subject^Finite

29. Generation Process: traversal imperative interrogative Finite^Subject
indicative
+Finite
declarative
Subject^Finite

30. Generation Process: traversal imperative interrogative Finite^Subject
indicative
+Finite
declarative
Subject^Finite

31. Generation Process: traversal imperative interrogative Finite^Subject
indicative
+Finite
declarative
Subject^Finite

32. Generation Process: traversal interrogative Finite^Subject indicative

33. Generation Process:
structure
interrogative
Finite^Subject
+Finite

34. Generation Process:
structure
interrogative
Finite^Subject
+Finite

35. realization statements
Generation Process:
realization statements
Linear Precedence
Subject
Finite
[clause]
Finite^Subject
Are
you
going?
Immediate Dominance
+Finite
[interrogative]

36. Types of Realization Statements
Ordering (immediate, relative)
Structure building
Lexicalization

37. Motivated Grammatical
USER
Functionally
Motivated Grammatical
Choices

38. Motivated Grammatical
USER
Functionally
Motivated Grammatical
Choices
user = language engineer:
developing and debugging the
“grammatical competence”
of a language resource

39. Motivated Grammatical
USER
Functionally
Motivated Grammatical
Choices
Semantic
Specifications

40. Motivated Grammatical
USER
Functionally
Motivated Grammatical
Choices
Semantic
Specifications
user = system builder:
developing and debugging a
system that expects natural
language generation
functionality