Rhetorical Structure Model in Advanced Discourse Analysis
IraValerie2
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Jul 30, 2024
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About This Presentation
Linguistic Discourse Model
Slide Content
RHETORICAL
STRUCTURE
MODEL
STRUCTURE
MODEL
Rhetorical Structure Theory (RST) is a
framework in discourse analysis and
computational linguistics that aims to explain
the structure of texts in terms of hierarchical
relationships and rhetorical relations between
different parts of the text.
Definition
framework in discourse analysis and
computational linguistics that aims to explain
the structure of texts in terms of hierarchical
relationships and rhetorical relations between
different parts of the text.
Definition
RST focuses on how texts are organized to
convey meaning and coherence through the
identification of rhetorical relations that exist
between text spans.
Definition
convey meaning and coherence through the
identification of rhetorical relations that exist
between text spans.
Definition
In RST, texts are analyzed as hierarchically
structured units, with each unit consisting of a
nucleus and one or more satellite units. The
theory defines a set of rhetorical relations
(e.g., elaboration, contrast, cause-effect) that
describe the connections between these text
spans.
Definition
structured units, with each unit consisting of a
nucleus and one or more satellite units. The
theory defines a set of rhetorical relations
(e.g., elaboration, contrast, cause-effect) that
describe the connections between these text
spans.
Definition
By identifying these relations, RST helps
researchers understand how information is
structured and conveyed in written and
spoken discourse.
Definition
researchers understand how information is
structured and conveyed in written and
spoken discourse.
Definition
Rhetorical Structure Theory was developed in
the 1980s by William C. Mann and Sandra A.
Thompson as a framework for analyzing text
structure and coherence
Background
the 1980s by William C. Mann and Sandra A.
Thompson as a framework for analyzing text
structure and coherence
Background
The theory was initially proposed to address
the need for a systematic approach to
understanding how texts are organized and
how information is linked together in
discourse.
Background
the need for a systematic approach to
understanding how texts are organized and
how information is linked together in
discourse.
Background
Hierarchical structure in discourse: RST posits
that texts are hierarchically structured, with
larger units composed of smaller units. This
hierarchical organization helps in
understanding how information is organized
within a text.
Overview of Rhetorical
Structure Theory
that texts are hierarchically structured, with
larger units composed of smaller units. This
hierarchical organization helps in
understanding how information is organized
within a text.
Overview of Rhetorical
Structure Theory
Relations between text spans: RST identifies
rhetorical relations that describe the
connections between different parts of a text.
These relations include elaboration, contrast,
cause-effect, and others, which help in
revealing how ideas are related to each other.
Overview of Rhetorical
Structure Theory
rhetorical relations that describe the
connections between different parts of a text.
These relations include elaboration, contrast,
cause-effect, and others, which help in
revealing how ideas are related to each other.
Overview of Rhetorical
Structure Theory
Nucleus and satellite units: RST defines text
spans as having a nucleus, which contains the
main idea, and one or more satellite units that
provide additional information or clarification
to the nucleus.
Overview of Rhetorical
Structure Theory
spans as having a nucleus, which contains the
main idea, and one or more satellite units that
provide additional information or clarification
to the nucleus.
Overview of Rhetorical
Structure Theory
Rhetorical relations: RST categorizes
relationships between text spans into
rhetorical relations, which provide insights
into how information is structured and how
different parts of a text contribute to the
overall meaning.
Overview of Rhetorical
Structure Theory
relationships between text spans into
rhetorical relations, which provide insights
into how information is structured and how
different parts of a text contribute to the
overall meaning.
Overview of Rhetorical
Structure Theory
Rhetorical Structure Theory is used to analyze and
understand discourse by providing a systematic
framework for examining the structure of texts. By
identifying the hierarchical organization of texts, the
relationships between different parts of the text, and
the rhetorical relations that connect these parts, RST
helps researchers uncover the underlying meaning
and coherence in written and spoken discourse.
Discussion on how RST is used to
analyze and understand discourse
understand discourse by providing a systematic
framework for examining the structure of texts. By
identifying the hierarchical organization of texts, the
relationships between different parts of the text, and
the rhetorical relations that connect these parts, RST
helps researchers uncover the underlying meaning
and coherence in written and spoken discourse.
Discussion on how RST is used to
analyze and understand discourse
It helps in text summarization by identifying the main
ideas and their supporting details.
It aids in argumentation analysis by revealing how
arguments are structured and supported within a
text.
RST is applied in various ways to
analyze and understand discourse:
ideas and their supporting details.
It aids in argumentation analysis by revealing how
arguments are structured and supported within a
text.
RST is applied in various ways to
analyze and understand discourse:
It assists in discourse parsing by providing a
framework for segmenting and analyzing texts at
different levels of granularity.
It is used in natural language processing tasks to
improve the understanding of text structure and
coherence.
RST is applied in various ways to
analyze and understand discourse:
framework for segmenting and analyzing texts at
different levels of granularity.
It is used in natural language processing tasks to
improve the understanding of text structure and
coherence.
RST is applied in various ways to
analyze and understand discourse:
RST is valuable for various applications in linguistic
research, including text analysis, discourse parsing,
summarization, and argumentation analysis.
The framework provided by RST contributes to the
advancement of computational linguistics, natural
language processing, and discourse studies.
By studying discourse through the lens of RST, researchers
can gain a deeper understanding of how language is used
to convey meaning and communicate effectively
Importance of RST in linguistic
research
research, including text analysis, discourse parsing,
summarization, and argumentation analysis.
The framework provided by RST contributes to the
advancement of computational linguistics, natural
language processing, and discourse studies.
By studying discourse through the lens of RST, researchers
can gain a deeper understanding of how language is used
to convey meaning and communicate effectively
Importance of RST in linguistic
research
Hierarchical structure in discourse:
Texts are organized into hierarchical structures with larger
units containing smaller units.
This hierarchical organization helps in understanding the
relationships between different parts of the text and how
they contribute to the overall meaning.
Each level of the hierarchy represents a different level of
importance or contribution to the discourse.
Basic Principles of Rhetorical
Structure Theory
Texts are organized into hierarchical structures with larger
units containing smaller units.
This hierarchical organization helps in understanding the
relationships between different parts of the text and how
they contribute to the overall meaning.
Each level of the hierarchy represents a different level of
importance or contribution to the discourse.
Basic Principles of Rhetorical
Structure Theory
Relations between text spans:
RST focuses on identifying and describing the
relationships between different parts of a text.
These relationships help in understanding how information
is connected and structured within the text.
By analyzing the relations between text spans, researchers
can uncover the underlying coherence and meaning of the
discourse.
Basic Principles of Rhetorical
Structure Theory
RST focuses on identifying and describing the
relationships between different parts of a text.
These relationships help in understanding how information
is connected and structured within the text.
By analyzing the relations between text spans, researchers
can uncover the underlying coherence and meaning of the
discourse.
Basic Principles of Rhetorical
Structure Theory
Nucleus and satellite units:
In RST, text spans are divided into nucleus and satellite
units.
The nucleus contains the main idea or central point of the
text.
Satellite units provide additional information, details, or
clarification to the nucleus, supporting and expanding
upon the main idea.
Basic Principles of Rhetorical
Structure Theory
In RST, text spans are divided into nucleus and satellite
units.
The nucleus contains the main idea or central point of the
text.
Satellite units provide additional information, details, or
clarification to the nucleus, supporting and expanding
upon the main idea.
Basic Principles of Rhetorical
Structure Theory
Rhetorical relations (e.g., elaboration, contrast, cause-effect):
RST defines a set of rhetorical relations that describe the connections
between text spans.
These relations include:
Elaboration: Providing further details or explanations about a specific topic.
Contrast: Highlighting differences or contradictions between ideas.
Cause-effect: Showing the relationship between a cause and its effect.
Condition: Describing the conditions under which a certain event or
situation occurs.
Evaluation: Expressing judgments or assessments of information presented
in the text.
Temporal: Relating events or actions in terms of time sequences.
Basic Principles of Rhetorical
Structure Theory
RST defines a set of rhetorical relations that describe the connections
between text spans.
These relations include:
Elaboration: Providing further details or explanations about a specific topic.
Contrast: Highlighting differences or contradictions between ideas.
Cause-effect: Showing the relationship between a cause and its effect.
Condition: Describing the conditions under which a certain event or
situation occurs.
Evaluation: Expressing judgments or assessments of information presented
in the text.
Temporal: Relating events or actions in terms of time sequences.
Basic Principles of Rhetorical
Structure Theory
Text summarization: RST can be used to identify the
hierarchical structure of a text, helping in creating
concise and coherent summaries of longer texts.
Argumentation analysis: RST can assist in analyzing
and understanding the structure of arguments within a
text, helping to identify key points, claims, and
supporting evidence.
Applications of Rhetorical Structure
Theory
hierarchical structure of a text, helping in creating
concise and coherent summaries of longer texts.
Argumentation analysis: RST can assist in analyzing
and understanding the structure of arguments within a
text, helping to identify key points, claims, and
supporting evidence.
Applications of Rhetorical Structure
Theory
Discourse parsing: RST is useful in parsing and
understanding the structure of discourses, helping to
identify relationships between different parts of a text
and how they contribute to the overall meaning.
Natural language processing (NLP): RST can be
integrated into NLP systems to improve the
understanding of text organization and coherence,
leading to better text generation, sentiment analysis,
and information extraction.
Applications of Rhetorical Structure
Theory
understanding the structure of discourses, helping to
identify relationships between different parts of a text
and how they contribute to the overall meaning.
Natural language processing (NLP): RST can be
integrated into NLP systems to improve the
understanding of text organization and coherence,
leading to better text generation, sentiment analysis,
and information extraction.
Applications of Rhetorical Structure
Theory
THE
LINGUISTIC
DISCOURSE
MODEL
LINGUISTIC
DISCOURSE
MODEL
A linguistic discourse model refers to a
framework or structure used to analyze and
understand how language is used in
communication.
It focuses on how language is organized in
texts, conversations, or any form of
communication to convey meaning
Definition
framework or structure used to analyze and
understand how language is used in
communication.
It focuses on how language is organized in
texts, conversations, or any form of
communication to convey meaning
Definition
Discourse Analysis: Linguistic discourse
models are often used in discourse
analysis, which aims to study language
beyond the level of individual sentences
to understand how meaning is
constructed and interpreted in
communication.
KEY POINTS
models are often used in discourse
analysis, which aims to study language
beyond the level of individual sentences
to understand how meaning is
constructed and interpreted in
communication.
KEY POINTS
Context: These models take into account
the context in which language is used,
including social, cultural, and situational
factors that influence communication.
KEY POINTS
the context in which language is used,
including social, cultural, and situational
factors that influence communication.
KEY POINTS
Structure: They identify patterns, rules,
and structures within language use, such
as how sentences are connected to form
coherent texts or how turn-taking works
in conversations
KEY POINTS
and structures within language use, such
as how sentences are connected to form
coherent texts or how turn-taking works
in conversations
KEY POINTS
Coherence and Cohesion: Linguistic
discourse models look at how texts
maintain coherence (logical connection
of ideas) and cohesion (linguistic ties
that bind parts of a text together) to
ensure effective communication.
KEY POINTS
discourse models look at how texts
maintain coherence (logical connection
of ideas) and cohesion (linguistic ties
that bind parts of a text together) to
ensure effective communication.
KEY POINTS
Pragmatics: They also consider
pragmatic aspects of language use, such
as implicatures, speech acts, and
conversational implicature, to
understand how meaning is conveyed
beyond the literal interpretation of
words.
KEY POINTS
pragmatic aspects of language use, such
as implicatures, speech acts, and
conversational implicature, to
understand how meaning is conveyed
beyond the literal interpretation of
words.
KEY POINTS
Discourse Markers: These models may
explore the role of discourse markers
(e.g., "however," "therefore") in guiding
the flow of conversation or text and
signaling relationships between different
parts of discourse.
KEY POINTS
explore the role of discourse markers
(e.g., "however," "therefore") in guiding
the flow of conversation or text and
signaling relationships between different
parts of discourse.
KEY POINTS
Critical Discourse Analysis: Some
linguistic discourse models may take a
critical approach to analyzing language
use, focusing on power dynamics,
ideology, and social structures
embedded in communication.
KEY POINTS
linguistic discourse models may take a
critical approach to analyzing language
use, focusing on power dynamics,
ideology, and social structures
embedded in communication.
KEY POINTS
1. Understanding Communication:
Linguistic discourse models help us
understand how language is used to convey
meaning in different contexts, whether in
written texts, spoken conversations, or
other forms of communication.
IMPORTANCE
Linguistic discourse models help us
understand how language is used to convey
meaning in different contexts, whether in
written texts, spoken conversations, or
other forms of communication.
IMPORTANCE
2. Analyzing Texts: They allow researchers
to analyze texts and conversations at a
deeper level, looking beyond individual
sentences to uncover patterns, structures,
and relationships that shape meaning.
IMPORTANCE
to analyze texts and conversations at a
deeper level, looking beyond individual
sentences to uncover patterns, structures,
and relationships that shape meaning.
IMPORTANCE
3. Interpreting Intentions: By examining
language use through discourse models, we
can better interpret the intentions, beliefs,
attitudes, and emotions of speakers or
writers, leading to more accurate
understanding of communication.
IMPORTANCE
language use through discourse models, we
can better interpret the intentions, beliefs,
attitudes, and emotions of speakers or
writers, leading to more accurate
understanding of communication.
IMPORTANCE
4. Enhancing Language Teaching:
Educators can use linguistic discourse
models to teach students about the
nuances of language use, coherence,
cohesion, and pragmatics, helping them
become more effective communicators.
IMPORTANCE
Educators can use linguistic discourse
models to teach students about the
nuances of language use, coherence,
cohesion, and pragmatics, helping them
become more effective communicators.
IMPORTANCE
5. Improving Communication Skills:
Understanding discourse models can
enhance individuals' communication skills
by making them more aware of how
language functions in different contexts
and how to structure their own
communication effectively.
IMPORTANCE
Understanding discourse models can
enhance individuals' communication skills
by making them more aware of how
language functions in different contexts
and how to structure their own
communication effectively.
IMPORTANCE
6. Cultural Insights: Discourse models can
also provide insights into cultural
differences in communication styles, norms,
and conventions, helping to bridge
communication gaps in multicultural
settings.
IMPORTANCE
also provide insights into cultural
differences in communication styles, norms,
and conventions, helping to bridge
communication gaps in multicultural
settings.
IMPORTANCE
7. Research and Analysis: Researchers in
fields such as linguistics, sociology,
anthropology, and communication studies
rely on discourse models to conduct in-
depth analyses of language use, social
interactions, and power dynamics in
communication.
IMPORTANCE
fields such as linguistics, sociology,
anthropology, and communication studies
rely on discourse models to conduct in-
depth analyses of language use, social
interactions, and power dynamics in
communication.
IMPORTANCE
8. Critical Thinking: By applying discourse
models, individuals can develop critical
thinking skills by examining language use
critically, questioning assumptions, and
uncovering underlying meanings in
communication.
IMPORTANCE
models, individuals can develop critical
thinking skills by examining language use
critically, questioning assumptions, and
uncovering underlying meanings in
communication.
IMPORTANCE
9. Professional Applications: Discourse
models are used in various professional
fields, such as marketing, politics, law, and
media, to analyze and shape communication
strategies, messages, and narratives.
IMPORTANCE
models are used in various professional
fields, such as marketing, politics, law, and
media, to analyze and shape communication
strategies, messages, and narratives.
IMPORTANCE
Micro-level discourse refers to the
smallest unit of analysis within a
conversation or text. It focuses on the
specific linguistic elements and structures
that contribute to the overall meaning and
coherence of a discourse.
Micro-level Discourse
smallest unit of analysis within a
conversation or text. It focuses on the
specific linguistic elements and structures
that contribute to the overall meaning and
coherence of a discourse.
Micro-level Discourse
1. Lexical Choices: Micro-level discourse
analysis involves examining the specific
words chosen by the speaker or writer and
their impact on the meaning of the
discourse.
Micro-level Discourse
analysis involves examining the specific
words chosen by the speaker or writer and
their impact on the meaning of the
discourse.
Micro-level Discourse
2. Grammar and Syntax: It includes
analyzing the grammar and syntax of
sentences at a detailed level to
understand how they contribute to the
overall structure of the discourse.
Micro-level Discourse
analyzing the grammar and syntax of
sentences at a detailed level to
understand how they contribute to the
overall structure of the discourse.
Micro-level Discourse
3. Pragmatics: Micro-level discourse also
considers the pragmatic aspects of
language use, such as the implications of
specific speech acts, conversational
implicatures, and presuppositions.
Micro-level Discourse
considers the pragmatic aspects of
language use, such as the implications of
specific speech acts, conversational
implicatures, and presuppositions.
Micro-level Discourse
4. Discourse Markers: Analysis at the
micro-level involves looking at discourse
markers and connectives that signal
relationships between different parts of a
discourse.
Micro-level Discourse
micro-level involves looking at discourse
markers and connectives that signal
relationships between different parts of a
discourse.
Micro-level Discourse
5. Turn-Taking: It includes examining the
dynamics of turn-taking in conversations,
including the ways speakers signal the
beginning and end of their turns.
Micro-level Discourse
dynamics of turn-taking in conversations,
including the ways speakers signal the
beginning and end of their turns.
Micro-level Discourse
6. Coherence and Cohesion: Micro-level
discourse analysis focuses on how
linguistic elements such as pronouns,
conjunctions, and lexical repetitions
contribute to the coherence and cohesion
of a discourse.
Micro-level Discourse
discourse analysis focuses on how
linguistic elements such as pronouns,
conjunctions, and lexical repetitions
contribute to the coherence and cohesion
of a discourse.
Micro-level Discourse
Meso-level discourse refers to an
intermediate level of analysis that falls
between micro-level and macro-level
discourse. It involves examining larger
segments of discourse such as paragraphs,
conversations, or exchanges, rather than
focusing on individual words or sentences.
Meso-Level Discourse
intermediate level of analysis that falls
between micro-level and macro-level
discourse. It involves examining larger
segments of discourse such as paragraphs,
conversations, or exchanges, rather than
focusing on individual words or sentences.
Meso-Level Discourse
1. Segmentation: Meso-level discourse
analysis involves segmenting the discourse
into meaningful units, such as paragraphs,
turns in a conversation, or thematic sections.
Meso-Level Discourse
analysis involves segmenting the discourse
into meaningful units, such as paragraphs,
turns in a conversation, or thematic sections.
Meso-Level Discourse
2. Coherence and Progression: It focuses on
the coherence and progression of ideas within
these larger segments, looking at how they are
connected and how they contribute to the
overall meaning of the discourse.
Meso-Level Discourse
the coherence and progression of ideas within
these larger segments, looking at how they are
connected and how they contribute to the
overall meaning of the discourse.
Meso-Level Discourse
3. Discourse Structure: Meso-level discourse
analysis considers the overall structure of the
discourse, including the organization of
information, the flow of ideas, and the
development of arguments or narratives.
Meso-Level Discourse
analysis considers the overall structure of the
discourse, including the organization of
information, the flow of ideas, and the
development of arguments or narratives.
Meso-Level Discourse
4. Topic Development: It involves analyzing
how topics are introduced, developed, and
concluded within the larger segments of
discourse.
Meso-Level Discourse
how topics are introduced, developed, and
concluded within the larger segments of
discourse.
Meso-Level Discourse
5. Discourse Strategies: Meso-level discourse
analysis examines the use of discourse
strategies such as summarizing, elaborating,
contrasting, or transitioning between topics
within a segment of discourse.
Meso-Level Discourse
analysis examines the use of discourse
strategies such as summarizing, elaborating,
contrasting, or transitioning between topics
within a segment of discourse.
Meso-Level Discourse
Macro-level discourse refers to the
highest level of analysis that looks at the
broader context, social factors, and
overarching structures that influence and
shape discourse.
Macro-Level Discourse
highest level of analysis that looks at the
broader context, social factors, and
overarching structures that influence and
shape discourse.
Macro-Level Discourse
1. Social Context: Macro-level discourse
analysis considers the social, cultural, and
historical context in which a discourse
takes place. It looks at how societal norms,
power dynamics, and ideologies influence
language use.
Macro-Level Discourse
analysis considers the social, cultural, and
historical context in which a discourse
takes place. It looks at how societal norms,
power dynamics, and ideologies influence
language use.
Macro-Level Discourse
2. Discourse Communities: It examines
how discourse is shaped by the
characteristics and norms of specific
discourse communities, including
professional groups, social networks, or
cultural subgroups
Macro-Level Discourse
how discourse is shaped by the
characteristics and norms of specific
discourse communities, including
professional groups, social networks, or
cultural subgroups
Macro-Level Discourse
3. Genre and Register: Macro-level
discourse analysis looks at how discourse
is influenced by genre conventions and
linguistic registers, which vary across
different communicative contexts.
Macro-Level Discourse
discourse analysis looks at how discourse
is influenced by genre conventions and
linguistic registers, which vary across
different communicative contexts.
Macro-Level Discourse
4. Power Dynamics: It considers how
power structures and inequalities
manifest in discourse, including how
language can be used to exert control,
authority, or resistance.
Macro-Level Discourse
power structures and inequalities
manifest in discourse, including how
language can be used to exert control,
authority, or resistance.
Macro-Level Discourse
5. Discourse Practices: Macro-level
analysis involves studying broader
patterns of discourse practices within a
society or community, such as storytelling
traditions, political rhetoric, or media
discourse
Macro-Level Discourse
analysis involves studying broader
patterns of discourse practices within a
society or community, such as storytelling
traditions, political rhetoric, or media
discourse
Macro-Level Discourse
6. Discourse Ideologies: It explores the
underlying beliefs, values, and ideologies
that shape discourse, including how
language is used to reinforce or challenge
dominant discourses.
Macro-Level Discourse
underlying beliefs, values, and ideologies
that shape discourse, including how
language is used to reinforce or challenge
dominant discourses.
Macro-Level Discourse
7. Language Policy and Planning: Macro-
level discourse analysis includes
examining language policies, planning
initiatives, and language attitudes that
influence the use of language in society.
Macro-Level Discourse
level discourse analysis includes
examining language policies, planning
initiatives, and language attitudes that
influence the use of language in society.
Macro-Level Discourse
A. Corpus Linguistics:
Corpus linguistics is the study of language based on large
collections of "real-life" language use stored in corpora (or
corpuses). Corpora are computerized databases created
for linguistic research.
It goes beyond individual sentences and examines
patterns of form and meaning in context. In other words,
it looks at how language is used in various situations.
Analytical Tools and
Methods
Corpus linguistics is the study of language based on large
collections of "real-life" language use stored in corpora (or
corpuses). Corpora are computerized databases created
for linguistic research.
It goes beyond individual sentences and examines
patterns of form and meaning in context. In other words,
it looks at how language is used in various situations.
Analytical Tools and
Methods
A. Corpus Linguistics:
Researchers use corpus linguistics to analyze language
features, such as vocabulary, grammar, and textual
patterns, across different genres and social contexts.
Examples of materials suitable for corpus linguistics
include books, newspapers, marketing materials, business
documents, websites, interviews, and conversations.
Analytical Tools and
Methods
Researchers use corpus linguistics to analyze language
features, such as vocabulary, grammar, and textual
patterns, across different genres and social contexts.
Examples of materials suitable for corpus linguistics
include books, newspapers, marketing materials, business
documents, websites, interviews, and conversations.
Analytical Tools and
Methods
B. Conversation Analysis:
Conversation analysis (CA) focuses on spoken and written language
produced during ordinary human interactions. Sociologist Harvey
Sacks is credited with founding this discipline.
CA examines how people come together, exchange information,
negotiate, and maintain social relations through conversation.
One key concept in CA is the adjacency pair, which consists of a
call and a response.
Analytical Tools and
Methods
Conversation analysis (CA) focuses on spoken and written language
produced during ordinary human interactions. Sociologist Harvey
Sacks is credited with founding this discipline.
CA examines how people come together, exchange information,
negotiate, and maintain social relations through conversation.
One key concept in CA is the adjacency pair, which consists of a
call and a response.
Analytical Tools and
Methods
C. Critical Discourse Analysis:
Critical discourse analysis (CDA) examines written or spoken language in
relation to its social context. It aims to understand how language is used
in real-life situations.
Researchers analyze language to uncover underlying meanings, cultural
rules, and assumptions. CDA investigates issues affecting individuals
negatively, such as financial inequality.
CDA posits that social reality is socially constructed, emphasizing
subjective viewpoints. It goes beyond literal word meanings and
considers broader social, political, and historical contexts
Analytical Tools and
Methods
Critical discourse analysis (CDA) examines written or spoken language in
relation to its social context. It aims to understand how language is used
in real-life situations.
Researchers analyze language to uncover underlying meanings, cultural
rules, and assumptions. CDA investigates issues affecting individuals
negatively, such as financial inequality.
CDA posits that social reality is socially constructed, emphasizing
subjective viewpoints. It goes beyond literal word meanings and
considers broader social, political, and historical contexts
Analytical Tools and
Methods
D. Discourse Modeling Techniques:
Discourse modeling techniques involve studying how people use
language in different situations to understand their intended meanings
and messages.
These techniques help create social relationships and cultural norms by
examining language patterns and their effects.
Researchers analyze discourse to uncover how language serves as a
means of prompting social change or achieving specific goals.
Analytical Tools and
Methods
Discourse modeling techniques involve studying how people use
language in different situations to understand their intended meanings
and messages.
These techniques help create social relationships and cultural norms by
examining language patterns and their effects.
Researchers analyze discourse to uncover how language serves as a
means of prompting social change or achieving specific goals.
Analytical Tools and
Methods
STRUCTURE
DISCOURSE
REPRESENTATION
THEORY
DISCOURSE
REPRESENTATION
THEORY
Structure Discourse Representation Theory (SDRT) is a
linguistic framework that extends the principles of
Discourse Representation Theory (DRT.
DRT posits that the meaning of a sentence is determined
by the context in which it is used, emphasizing the role of
context change potential (ccp) in interpreting discourse.
SDRT builds upon DRT by incorporating additional
features related to discourse structure and pragmatic
interpretation
Definition and Background
linguistic framework that extends the principles of
Discourse Representation Theory (DRT.
DRT posits that the meaning of a sentence is determined
by the context in which it is used, emphasizing the role of
context change potential (ccp) in interpreting discourse.
SDRT builds upon DRT by incorporating additional
features related to discourse structure and pragmatic
interpretation
Definition and Background
Unlike DRT, which focuses on logical structure
and anaphora resolution, SDRT considers
rhetorical relations and their impact on discourse
coherence.
SDRT aims to model how discourse unfolds over
time, accounting for both linguistic and pragmatic
factors
Definition and Background
and anaphora resolution, SDRT considers
rhetorical relations and their impact on discourse
coherence.
SDRT aims to model how discourse unfolds over
time, accounting for both linguistic and pragmatic
factors
Definition and Background
Discourse Coherence:
SDRT emphasizes the interplay between discourse
interpretation and coherence.
It considers how discourse relations (such as
elaboration, contrast, or cause-effect) contribute to
the overall coherence of a text.
By analyzing these relations, SDRT helps explain how
sentences connect and form a coherent discourse.
Importance and Applications
SDRT emphasizes the interplay between discourse
interpretation and coherence.
It considers how discourse relations (such as
elaboration, contrast, or cause-effect) contribute to
the overall coherence of a text.
By analyzing these relations, SDRT helps explain how
sentences connect and form a coherent discourse.
Importance and Applications
Abstract Entity Anaphora:
Anaphora refers to the reference of an expression
(e.g., pronouns) to a previously mentioned entity.
SDRT extends DRT to handle a wider range of
anaphoric expressions, including abstract entities
(e.g., events, propositions, or situations).
It provides a framework for understanding how
abstract anaphora is resolved within discourse
Importance and Applications
Anaphora refers to the reference of an expression
(e.g., pronouns) to a previously mentioned entity.
SDRT extends DRT to handle a wider range of
anaphoric expressions, including abstract entities
(e.g., events, propositions, or situations).
It provides a framework for understanding how
abstract anaphora is resolved within discourse
Importance and Applications
Abstract Entity Anaphora:
Anaphora refers to the reference of an expression
(e.g., pronouns) to a previously mentioned entity.
SDRT extends DRT to handle a wider range of
anaphoric expressions, including abstract entities
(e.g., events, propositions, or situations).
It provides a framework for understanding how
abstract anaphora is resolved within discourse
Importance and Applications
Anaphora refers to the reference of an expression
(e.g., pronouns) to a previously mentioned entity.
SDRT extends DRT to handle a wider range of
anaphoric expressions, including abstract entities
(e.g., events, propositions, or situations).
It provides a framework for understanding how
abstract anaphora is resolved within discourse
Importance and Applications
Meeting Points in Transportation Systems:
Beyond linguistics, SDRT has practical
applications. For example, it has been used to
optimize shared demand-responsive
transportation (SDRT) systems.
SDRT helps determine optimal meeting points for
customer pick-up and drop-off, considering
factors like walking distances, waiting times, and
operator resources.
Importance and Applications
Beyond linguistics, SDRT has practical
applications. For example, it has been used to
optimize shared demand-responsive
transportation (SDRT) systems.
SDRT helps determine optimal meeting points for
customer pick-up and drop-off, considering
factors like walking distances, waiting times, and
operator resources.
Importance and Applications
Utterances: The basic unit of information in DRT is
an utterance, which can be a sentence or a part of
a sentence.
Discourse Referents: Entities mentioned in the
utterances are represented as discourse
referents, which can be individuals, objects, or
concepts.
Basic Components of DRT:
an utterance, which can be a sentence or a part of
a sentence.
Discourse Referents: Entities mentioned in the
utterances are represented as discourse
referents, which can be individuals, objects, or
concepts.
Basic Components of DRT:
Semantic Composition: DRT provides a formal
mechanism for composing the meaning of
individual sentences and integrating them into a
coherent representation of the entire discourse.
Role of DRT in Formal Semantics:
mechanism for composing the meaning of
individual sentences and integrating them into a
coherent representation of the entire discourse.
Role of DRT in Formal Semantics:
Scope Resolution: DRT helps resolve issues
related to quantifier scope ambiguity in natural
language by representing the scope of quantifiers
within a DRS.
Role of DRT in Formal Semantics:
related to quantifier scope ambiguity in natural
language by representing the scope of quantifiers
within a DRS.
Role of DRT in Formal Semantics:
Presuppositions and Anaphora Resolution: DRT is
useful in handling presuppositions (background
assumptions) and anaphora (pronouns referring
back to earlier noun phrases) by capturing the
relationships between different parts of a
discourse.
Role of DRT in Formal Semantics:
useful in handling presuppositions (background
assumptions) and anaphora (pronouns referring
back to earlier noun phrases) by capturing the
relationships between different parts of a
discourse.
Role of DRT in Formal Semantics:
Inference and Interpretation: DRT facilitates
inference and interpretation processes by
formalizing the structure of information in a
discourse and enabling the derivation of logical
consequences based on this structure.
Role of DRT in Formal Semantics:
inference and interpretation processes by
formalizing the structure of information in a
discourse and enabling the derivation of logical
consequences based on this structure.
Role of DRT in Formal Semantics:
Hierarchical Structure:
In Structure Discourse Representation Theory
(SDRT), information is structured hierarchically to
capture the organization and relationships within
a discourse.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
In Structure Discourse Representation Theory
(SDRT), information is structured hierarchically to
capture the organization and relationships within
a discourse.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Hierarchical Organization: Information in a
discourse is organized in a nested structure,
where different levels of information are linked
based on their relationships and dependencies.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
discourse is organized in a nested structure,
where different levels of information are linked
based on their relationships and dependencies.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Hierarchical Levels: SDRT represents information
at different levels of granularity, allowing for a
more nuanced understanding of how discourse
elements interact and contribute to the overall
meaning.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
at different levels of granularity, allowing for a
more nuanced understanding of how discourse
elements interact and contribute to the overall
meaning.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Example of Hierarchical Structure in SDRT:
A discourse about a family gathering may have
hierarchical levels representing different aspects
such as the attendees, activities, and
relationships among family members. Each level
contributes to the overall coherence of the
discourse.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
A discourse about a family gathering may have
hierarchical levels representing different aspects
such as the attendees, activities, and
relationships among family members. Each level
contributes to the overall coherence of the
discourse.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Constraints and Rules:
Constraints and rules in SDRT govern the
interpretation of a discourse by imposing
restrictions on how information can be structured
and connected within the discourse
representation.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Constraints and rules in SDRT govern the
interpretation of a discourse by imposing
restrictions on how information can be structured
and connected within the discourse
representation.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Constraints: These are conditions that must be
satisfied for a discourse representation to be
considered valid. Constraints ensure that the
discourse maintains coherence and consistency.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
satisfied for a discourse representation to be
considered valid. Constraints ensure that the
discourse maintains coherence and consistency.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Rules: Rules in SDRT define the relationships
between discourse elements, how they are linked,
and how they contribute to the overall meaning of
the discourse.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
between discourse elements, how they are linked,
and how they contribute to the overall meaning of
the discourse.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Example of Constraints and Rules in SDRT:
Pronoun Resolution: A rule in SDRT may specify
how a pronoun should be resolved by linking it to
its antecedent in the discourse. This rule helps
maintain referential coherence.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Pronoun Resolution: A rule in SDRT may specify
how a pronoun should be resolved by linking it to
its antecedent in the discourse. This rule helps
maintain referential coherence.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Quantifier Binding: Constraints in SDRT may
govern the binding of quantifiers within a
discourse to ensure that each quantifier is
correctly interpreted in relation to its scope and
context.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
govern the binding of quantifiers within a
discourse to ensure that each quantifier is
correctly interpreted in relation to its scope and
context.
Formal Representation in Structure
Discourse Representation Theory (SDRT)
Constraints and rules play a critical role in guiding
the interpretation process in SDRT, helping to
maintain coherence, resolve ambiguities, and
derive logical inferences from the discourse
representation.
Importance of Constraints and Rules in
SDRT:
the interpretation process in SDRT, helping to
maintain coherence, resolve ambiguities, and
derive logical inferences from the discourse
representation.
Importance of Constraints and Rules in
SDRT:
By enforcing constraints and following rules,
SDRT ensures that the discourse representation
accurately reflects the intended meaning of the
discourse and facilitates meaningful
interpretation by computational systems and
human readers.
Importance of Constraints and Rules in
SDRT:
SDRT ensures that the discourse representation
accurately reflects the intended meaning of the
discourse and facilitates meaningful
interpretation by computational systems and
human readers.
Importance of Constraints and Rules in
SDRT:
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