Chapter 20: Natural Language Generation

Presented by: Anastasia Gorbunova

LING538: Computational Linguistics, Fall 2006

Speech and Language Processing (Jurafsky & Martin)

Natural Language Generation(NLG)

The process of constructing natural language outputs from non-linguistic inputs - maps from meaning to text

Concerns: - choice

Natural Language Understanding(NLU)

The process of producing non-linguistic outputs from natural language inputshypothesis management - maps from text to meaning

Concerns: - ambiguity - under-specification - ill-formed input

Both must represent a range of lexical and grammatical forms required for the application domain

NLG

Choice Issues Architecture

Communicative Goal Knowledge Base

Discourse Planner Mechanisms for building Discourse Structures: - Text schemata; Rhetorical Relations Content Selection

Surface Realizer Approaches: - Systemic Grammar; - Functional Unification Grammar

Natural Language Output

Microplanning

Lexical Selection

Context Selection

Discourse Structure

Sentence Structure-referring expressions

-aggregation

Output from DP

Input to SR

Surface Realizer Produces ordered sequences of words as constrained by the rules of lexicon and grammar.

Approaches:

Systemic Grammar Functional Unification Grammar

• Treats language as resource for expressingmeaning in context • Represents sentences as collections of functions and maintains rules for mapping those functions onto explicit grammatical forms • Expressed as a system network

Surface Realizer Produces ordered sequences or words as constrained by the rules of lexicon and grammar.

Approaches:

Systemic Grammar Functional Unification Grammar

• Treats language as resource for expressingmeaning in context • Represents sentences as collections of functions and maintains rules for mapping those functions onto explicit grammatical forms • Expressed as a system network

• Builds generational grammar as a feature structure with potential alternations • Then unifies it with input specification built using the same sort of feature structure• Expressed as an attribute-value matrix

ThemeTextual

TransitivityIdeational

MoodInterpersonalThe system will save the document

LayersMeta-

functions

ThemeTextual

TransitivityIdeational

MoodInterpersonalThe system will save the document

LayersMeta-

functions

rhemetheme

goalprocessactor

objectpredicatorfinitesubject

rhemetheme

goalprocessactor

objectpredicatorfinitesubject

Surface Realizer Produces ordered sequences or words as constrained by the rules of lexicon and grammar.

Approaches:

Systemic Grammar Functional Unification Grammar

Take input at different levels• Treats language as resource for expressingmeaning in context • Represents sentences as collections of functions and maintains rules for mapping those functions onto explicit grammatical forms • Expressed as a system network

Both grammars• use functional categorizations

- input is functionally rather than syntactically specified

• support multiple levels that are entered recursively during the generation process

• Builds generational grammar as a feature structure with potential alternations • Then unifies it with input specification built using the same sort of feature structure• Expressed as an attribute-value matrix• Input represented as a functional description:

ThemeTextual

TransitivityIdeational

MoodInterpersonalThe system will save the document

LayersMeta-

functions

ThemeTextual

TransitivityIdeational

MoodInterpersonalThe system will save the document

LayersMeta-

functions

rhemetheme

goalprocessactor

objectpredicatorfinitesubject

rhemetheme

goalprocessactor

objectpredicatorfinitesubject

NLG

Choice Issues Architecture

Communicative Goal Knowledge Base

Discourse Planner Mechanisms for building Discourse Structures: - Text schemata; Rhetorical Relations Content Selection

Surface Realizer Approaches: - Systemic Grammar; - Functional Unification Grammar

Natural Language Output

Microplanning

Lexical Selection

Context Selection

Discourse Structure

Sentence Structure-referring expressions

-aggregation

Output from DP

Input to SR

Discourse PlannerKeeps track of the focus and the local topic of discourse; considers relationships between

sentences. Also responsible for content selection and lexical selection

Mechanisms for building discourse structures: Text Schemata• Useful if a discrete set of consistent patternsand expressions can be found and encoded • May be represented as an augmented transition network

• Problems: - impractical when text calls for structural variety and richness of expression - resulting discourse structure includes no higher-level structure relating sentences together

S0

S1

S2

Є

Add Precondition

Express the Action

Recursively Add Sub-Step

Add Side-Effect

Rhetorical Relations •Rhetorical Structure Theory – text organization based on relationships between parts of text• RST relations: elaboration, contrast, condition, purpose, result, etc.• Used when the text being generated calls for variation • Can develop own schema based on a particular situation

NLG

Choice Issues Architecture

Communicative Goal Knowledge Base

Discourse Planner Mechanisms for building Discourse Structures: - Text schemata; Rhetorical Relations Content Selection

Surface Realizer Approaches: - Systemic Grammar; - Functional Unification Grammar

Natural Language Output

Microplanning

Lexical Selection

Context Selection

Discourse Structure

Sentence Structure-referring expressions

-aggregation

Output from DP

Input to SR

Microplanning

The link between the discourse planner output and the surface realizer input

Two main areas of concern:

Referring expressions - determine those aspects of an entity that should be used when referring to it in a particular context

Aggregation- apportioning the content from the knowledge base into phrase, clause, and sentence-sized chunks

NLG

Choice Issues Architecture

Communicative Goal Knowledge Base

Discourse Planner Mechanisms for building Discourse Structures: - Text schemata; Rhetorical Relations Content Selection

Surface Realizer Approaches: - Systemic Grammar; - Functional Unification Grammar

Natural Language Output

Microplanning

Lexical Selection

Context Selection

Discourse Structure

Sentence Structure-referring expressions

-aggregation

Output from DP

Input to SR