SlideShare une entreprise Scribd logo
1  sur  14
Télécharger pour lire hors ligne
Linguistic Theory Meets
Lexicography
Comprehension Questions
1.

Write the sense relationships which reflect the similarities between lexical
p
units.

2.

State the kinds of antonyms and explain each of them.

3.

Explain ‘frame semantics’ theory.

4.

What are the roles of the frames, frame elements and context?

5.

Which steps are involved during the analysis process carried out by using frame
semantics theory?

6.

What is the importance of using the frame semantics approach?

7.

Write the information types which are relevant to make a lexicographic record
of a word.

8.

What are the inherent properties of the headword?

9.

Why learning the properties of the source texts is sometimes needed?
5.1
5 1 Preliminaries
A grounding in linguistic theory is not a prerequisite for being a proficient
lexicographer – still less a guarantee of success i th fi ld
l i
h
till l
t
f
in the field.
But there are certain basic linguistic concepts which are invaluable in preparing
people to analyse data and to produce concise, accurate dictionary entries.
An awareness of linguistic theory can help lexicographers to do their jobs more
effectively and with greater confidence.
This chapter reviews those linguistic theories which we have found to have direct
application to our work as dictionary planners and dictionary makers.
5.2 Sense relationships: similarities
This section summarizes different types of ‘similarity’ between lexical units:
o

Th
th t h
ti
t
ti (hyponym and synonymy)
d
)
Those that share some semantic property or properties (h

o

Those that denote a part-whole relationship between objects in the real world (meronymy)

o

Those that allow similar metaphorical sense extensions (regular polysemy)

5.2.1
5 2 1 Hyponymy
The nodes of this hierarchy are the ‘superordinate’ and the ‘hyponym’.
This relationship can be summarized as ‘if a hyponym then a superordinate’.
Its major significance for lexicographers is that the ‘genus expression’ (the central
genus expression
word or words) in a definition should ideally be the superordinate of the headword.
Hyponymy rule of thumb: X is a Y but Y is not only an X (a terrier is a dog).
The hyponymy hierarchy is rarely found in adjectives, and consequently there is a real
lack of superordinates.
Cohyponyms rule of th b X and Y are both Zs ( rose and a tulip are both flowers).
C h
l f thumb:
d
b th Z (a
d t li
b th fl
)
5.2.2 Synonymy
Synonyms are words which have the same meaning like ‘pavement’ and ‘sidewalk’.
True synonyms are extremely rare; the nearest you get is usually a pseudo-synonymy and
l
h
ll
d
d
synonyms in dictionaries often turn out to be cohyponyms or superordinates.
Pure synonymy is rare across languages, except for the names of concrete objects which
the two cultures share.
Synonymy rule of thumb: X is Y and Y is X (shut is close and close is shut).
5.2.3 Meronymy
Meronymy reflects the relationship of the part to the whole and vice versa.
It’s difficult to define the part without mentioning the whole but the part is only
occasionally referred to in the definition of the whole.
Meronymy rule of thumb: X and other parts of Y.
Quasi-meronymy reflects the relationship of the member to the group or class of
people, or collection of objects.
This is a rather loose relationship: it’s difficult to word a formula appropriate to all the
cover.
varied Lus it should cover
Quasi-meronymy rule of thumb: X belongs to / in a Y.
5.2.4 Regular polysemy
Some polysemous words have a particular relationship with others i th i ‘l i l s t’ in
S
l s
s
ds h
ti l
l ti shi
ith th s in their ‘lexical set’ i
that several of their meanings seem to parallel each other.
Certain specific semantic components result in sets of words behaving lexicographically
in a very similar way. This is known as ‘regular polysemy’.
When you re planning the editorial work in a dictionary project it’s obciously a help to
you’re
project, it s
the team if you can list the major instances of regular polysemy, either by producing
template entries or simply by issuing lists of headwords related in this way.
English morphology encourages a wider range of regular polysemt than is found in
languages that have specific forms for verbs and nouns.
l
h h
ifi f
f
b
d
5.3 Sense relationships: differences
This section summarizes relationships between LUs that are in some way opposite in
h
l
h
b
L
h
meaning.
The kinds are complementary, polar and directional antonymy.
5.3.1
5 3 1 Complementary antonymy
This relationship is sometimes called ‘contradiction’.
Complementary antonymy rule of thumb: If it isn’t X then it must be Y and vice versa.
5 3 2 Polar antonymy
5.3.2
This relationship is similar to, but more complex than, complementarity.
There is a gradient between X and Y in polar antonymy. X and Y are at the poles of
gradient,
area,
this gradient but in between there is an indeterminate area where more X and less Y
are found.
Polar antonymy rule of thumb: If it’s X then it can’t be Y and vice versa, but it can be
somewhere in between.
5.3.3 Directional antonymy
Directional antonyms include various subtypes: some denote contrary movement or
position, for instance, pairs of words representing opposing poles along a shared axis.
5.3.4 Converseness
Converseness holds between pairs of words which have a certain semantic symmetry, so
that although not antonyms one of the pair is felt in some way to be linked by
g
y
p
y
y
oppositeness to the other.
There is little direct application of converse pairs in dictionaries, but if a word is
difficult to define a look at its converse’s definition can be helpful.
5.4 Frame semantics
The application of this theory to practical lexicography results in the approach to
lexicographic relevance which helps lexicographers to identify useful facts in corpus
texts.
This theory which was produced by Fillmore describes words, their various meanings,
and how these are combined with others to form the utterances and sentences of a
language.
Its aim is to analyse and record for each sense of a word or phrase, the full range of
its semantic and syntactic relations.
To do this they have devised a suite of codes denoting semantic roles (frame elements)
this,
and grammatical relationships, which allow them to document in detail the corpus
contexts in which a word is found.
The work is computer-assisted.
The frame semantics approach to word behaviour is the most helpful and appropriate
approach to corpus data, ensuring that the analysis is correctly carried out, and no vital
fact is overlooked.
5.4.1
5 4 1 What are frames and frame elements
Frame semantics describes the meanings of words and phrases in terms of the frame to
which they belong and the contexts in which these LUs are found.
A semantic frame is a schematic representation of a situation type together with a list of the typical
participants, props, and concepts that are to be found in such a situation; these are the semantic
roles, or frame elements (Fes).
The context is normally the phrase or clause and maximally the sentence in which the target word
clause,
appears in corpus data.
5.4.2 How is the analysis done?
There are several distinct steps in the analysis process:
o First, the frame is defined, and its core elements named and described.
o Next, a list is made of as many words as can be found which in one of their senses evoke that
frame.
o Then for each sense or LU a set of corpus sentences is extracted, in which the word is used in
Then,
sense,
LU,
extracted
the particular sense.
o Each sentence is annotated by marking off any section which instantiates an FE and by recording
for each FE thus identified:
o Its phrase type
o Its grammatical function
5.4.3 Why is this useful for lexicographers?
The frame semantics approach, grounded in a coherent theory, offers the possibility of a more
systematic less subjective way of analysing corpus data and gives us confidence that all relevant
systematic,
data,
features are being captured.
5.5 Lexicographic relevance
When looking at the concordances the corpus offers for a word we have to determine ‘what is
lexicographically relevant’?
We consider lexicographic relevance from the standpoint of Fillmore’s frame semantics.
Three types of information are relevant to making a lexicographic record of a word:
o

What we know, as native speakers, about the headword (its inherent properties)

o

What we learn from its use in corpora and elsewhere (its contextual features)

o

What we know about where the citations came from (the properties of the source texts)

It’s important to remember that ‘lexicographic relevance’ relates to what is relevant to an
LU, and not to a lemma, the focus is the headword in one of its senses, not the whole word.
5.5.1 Inherent properties of the headword
This is the knowledge of our language that we all bring to analysing the corpus data and
writing the dictionary entry.
The properties of the headword that principally concern us can be summarized very briefly:
o

Its wordclass

o

Its wordforms

o

Its grammatical behaviour

o

Its semantics

In corpus lexicography we use our inherent knowledge of the headword rather to help us
discover the really useful facts in the corpus, and make sure the entry is comprehensive and
h
l
l
i
i
k
the examples are pleasing to our native speakers’’ ears.
Our knowledge of the headword’s inherent properties serves as quality control during our
work on corpus data, as we discover and record its contextual features in each of its LUs.
5.5.2 Contextual features of the headword
An understanding of lexicographic relevance helps you identify in a corpus sentence all the
essential components of the headword’s context, all the facts that you need to take into
account when writing any entry for that word.
5.5.2.1 Case study: argue
The headword argue contains four LUs; each represents a distinct sense of the
headword.
headword
LU 1: the sense of ‘quarrel, dispute’, the communication frame.
LU 2: the sense of ‘maintain, make a case for’, the reasoning frame.
LU 3: the sense of ‘indicate’, the evidence frame
indicate
frame.
LU 4: the sense of ‘persuade’, the persuasion frame.
They will differ for each LU, since the frame elements depend on the frame the LU
belongs to.
ongs
participant 1

participant 2

topic

The sentence is ‘Sam / was arguing / with his brother / about the money’.
We have to examine its;
o Frame elements or semantic roles
o Phrase types
o Grammatical function
Frame elements:

Participant 1
Participant 2
Topic

Sam
with his brother

about the money

Phrase types + grammatical functions
NP: Subject / PP-with: Complement / PP-about: Complement
The phrase type information allows you to mark off in the sentence the actual sections
relevant to your description.
The information about grammatical function lets you assess the importance of the
component for your database.
The set of threefold descriptions of each component contains most of the
information you need to extract from this sentance for your database.
Whan we are analysing corpus data in an attempt to collect the facts about a
word for our dictionary entry, it’s important to be able to discover from the
concordances tha actual source of each citation.
This information is stored in the ‘document headers’ of each text in the corpus.
Using this information the computer can tell you whether a particular citation
comes mainly from spoken or written language, or political documents, or feminist
publications and so on.
If you h
have any d b about the way a word i used, i ’ useful to b able to
doubts b
h
d is
d it’s
f l
be bl
check up on where the citation came from.
To summarize lexicographic relevance: the wordclass of the word is central to
what is relevant to record, and there are lists of the principal co constituents of
record
co-constituents
a clause that are relevant for each of the four major wordclasses.
Turkish Summary
Bu bölümde sözlük oluşturan kişilerin çalışmalarına katkı sağlayabilecek bazı
ş
ş
ç ş
ğ y
dilbilimsel kuramlardan ve bu kuramların uygulanış biçimlerinden bahsedilmektedir.
Sözcükler arasında birtakım anlamsal ilişkiler vardır ve bu ilişkiler benzerlik ve
farklılıklara göre şekillenir. Sözcükler arasındaki benzerlikten doğan ilişkiler
sözcüklerin bazı anlambilimsel özellikleri paylaşmalarına nesneler arasındaki
paylaşmalarına,
parça-bütün ilişkilerine ve sözcüklerin benzer mecazi alt anlamları
çağrıştırmalarına göre farklılık gösterir. Sözcükler arasındaki farklılıklardan
doğan ilişkiler ise sözcüklerin birbirlerini zıtlıklarla tamamlamalarına, tamamen
farklı kavramları çağrıştırmalarına ve birbirlerine zıt olmalarına göre farklılık
gösterir. Dilbilimci Fillmore sözlükbilime de uygulanabilen ve ‘yapısal anlambilim’
olarak adlandırılan bir kuram geliştirmiştir. Bu kuram sözcükleri ve onların farklı
anlamlarını tasvir eder ve bir dildeki sözce ve tümcelerin oluşturulması için
ükl i diğ
ükl l
l birleştirilmesi gerektiğini açıklar. Bunu yapmak
i il
i
k iği i
kl
B
k
sözcüklerin diğer sözcüklerle nasıl bi l
için de anlambilimsel rolleri ve dilbilgisel ilişkileri gösteren bazı kodlar tasarlanır.
Bu kuramın sözlükbilime uygulanması sonucunda sözlükbilimcilere bütünce
metnindeki faydalı bilgileri tanımlama konusunda yardımcı olan sözlükbilimsel ilişki
y
g
y
ş
yaklaşımı ortaya çıkmıştır. Bir sözcüğün sözlükbilimsel ilişkilerini belirlemek için
sözcüğün genel özelliklerinin, bağlamsal özelliklerinin ve kaynak metinlerin
özelliklerinin bilinmesi gereklidir.
Comprehension Questions / Answers
Write the sense relationships which reflect the similarities between lexical
units.
Different types of ‘similarity’ between lexical units:
o

Those that share some semantic property or properties (hyponym and synonymy)

o

Those that denote a part-whole relationship between objects in the real world (meronymy)

o

Those that allow similar metaphorical sense extensions (regular polysemy)

State the kinds of antonyms and explain each of them.
The kinds are complementary, polar and directional antonymy.
Complementary antonymy
This relationship is sometimes called ‘contradiction’.
Complementary antonymy rule of thumb: If it isn’t X then it must be Y and vice versa.
P l antonymy
t
Polar
This relationship is similar to, but more complex than, complementarity.
There is a gradient between X and Y in polar antonymy. X and Y are at the poles of this
gra nt, ut n tw n th r s
gradient, but in between there is an indeterminate ar a, where more X and less Y ar foun .
n t rm nat area, wh r mor
an
ss are found.
Polar antonymy rule of thumb: If it’s X then it can’t be Y and vice versa, but it can be
somewhere in between.
Directional antonymy
Directional antonyms include various subtypes: some denote contrary movement or position,
for instance, pairs of words representing opposing poles along a shared axis.

Explain ‘frame semantics’ theory.
This theory which was produced by Fillmore describes words, their various meanings, and how
these are combined with others to form the utterances and sentences of a language. Its aim is
to analyse and record for each sense of a word or phrase, the full range of its semantic and
syntactic relations.

What are the roles of the frames, frame elements and context?
A semantic frame is a schematic representation of a situation type together with a list of the
typical participants, props, and concepts that are to be found in such a situation; these are
the semantic roles, or frame elements (Fes). The context is normally the phrase or clause and
roles
(Fes)
clause,
maximally the sentence in which the target word appears in corpus data.

Which steps are involved during the analysis process carried out by using frame
semantics theory?
There are several distinct steps in the analysis process:
o First, the frame is defined, and its core elements named and described.
o Next, a list is made of as many words as can be found which in one of their senses evoke
that f
th t frame.
o Then, for each sense, or LU, a set of corpus sentences is extracted, in which the word is
used in the particular sense.
o Each sentence is annotated by marking off any section which instantiates an FE and by
y
g
y
y
recording for each FE thus identified:
o Its phrase type
o Its grammatical function

What is the importance of using the frame semantics approach?
The frame semantics approach, grounded in a coherent theory, offers the possibility of a
more systematic, less subjective way of analysing corpus data, and gives us confidence that
all relevant features are being captured.

Write the information types which are relevant to make a lexicographic record
of a word.
Three types of information are relevant to making a lexicographic record of a word:
o What we know, as native speakers, about the headword (its inherent properties)
o What we learn from its use in corpora and elsewhere (its contextual features)
o Wh we know about where the citations came from (the properties of the source
What
k
b
h
h i i
f
( h
i
f h
texts)
What are the inherent properties of the headword?
The properties of the headword that principally concern us can be summarized very
briefly:
o Its wordclass
o Its wordforms
ts wor forms
o Its grammatical behaviour
o Its semantics
Why learning the properties of the source texts is sometimes needed?
Using this information the computer can tell you whether a particular citation comes
mainly from spoken or written language, or political documents, or feminist publications
and so on. If you have any doubts about the way a word is used, it’s useful to be able to
check up on where the citation came from
from.

Contenu connexe

Tendances

Morphology-Syntax Interface
Morphology-Syntax InterfaceMorphology-Syntax Interface
Morphology-Syntax InterfaceDr. Mohsin Khan
 
Three main aspects of stylistics
Three main aspects of stylisticsThree main aspects of stylistics
Three main aspects of stylisticsmj_llanto
 
Linguistic theories approaches and methods
Linguistic theories approaches and methodsLinguistic theories approaches and methods
Linguistic theories approaches and methodsEsraaAlobali
 
Suprasegmental phonology (revision)
Suprasegmental phonology (revision)Suprasegmental phonology (revision)
Suprasegmental phonology (revision)esraa bahaa
 
Introduction to linguistics lec 1
Introduction to linguistics lec 1Introduction to linguistics lec 1
Introduction to linguistics lec 1Hina Honey
 
Words sentences and dictionaryes by:Diana Villarreal
Words sentences and dictionaryes by:Diana VillarrealWords sentences and dictionaryes by:Diana Villarreal
Words sentences and dictionaryes by:Diana Villarreal12diana1993
 
Properties of human language
Properties of human language Properties of human language
Properties of human language abdul wahid
 
Word vs lexeme by james jamie 2014 presentation assigned by asifa memon lect...
Word vs lexeme  by james jamie 2014 presentation assigned by asifa memon lect...Word vs lexeme  by james jamie 2014 presentation assigned by asifa memon lect...
Word vs lexeme by james jamie 2014 presentation assigned by asifa memon lect...James Jamie
 
Systemic Functional Grammar
Systemic Functional Grammar Systemic Functional Grammar
Systemic Functional Grammar Sugeng Hariyanto
 
Prague school slides
Prague school slidesPrague school slides
Prague school slidesnoreen zafar
 
Introduction to Suprasegmental Features
Introduction to Suprasegmental FeaturesIntroduction to Suprasegmental Features
Introduction to Suprasegmental FeaturesNoramaliah Mohd Rahim
 
A Brief Introduction of Morphology
 A Brief Introduction of Morphology A Brief Introduction of Morphology
A Brief Introduction of Morphologyamna-shahid
 

Tendances (20)

Morphology-Syntax Interface
Morphology-Syntax InterfaceMorphology-Syntax Interface
Morphology-Syntax Interface
 
Root, base and stem
Root, base and stemRoot, base and stem
Root, base and stem
 
Generative grammar
Generative grammarGenerative grammar
Generative grammar
 
MORPHOLOGICAL PROCESS
MORPHOLOGICAL PROCESSMORPHOLOGICAL PROCESS
MORPHOLOGICAL PROCESS
 
Base root and stem
Base root and stemBase root and stem
Base root and stem
 
Three main aspects of stylistics
Three main aspects of stylisticsThree main aspects of stylistics
Three main aspects of stylistics
 
Transformational Generative Grammar
Transformational Generative GrammarTransformational Generative Grammar
Transformational Generative Grammar
 
Tree diagram
Tree diagramTree diagram
Tree diagram
 
Linguistic theories approaches and methods
Linguistic theories approaches and methodsLinguistic theories approaches and methods
Linguistic theories approaches and methods
 
Suprasegmental phonology (revision)
Suprasegmental phonology (revision)Suprasegmental phonology (revision)
Suprasegmental phonology (revision)
 
Introduction to linguistics lec 1
Introduction to linguistics lec 1Introduction to linguistics lec 1
Introduction to linguistics lec 1
 
The London School of Linguistics
The London School of LinguisticsThe London School of Linguistics
The London School of Linguistics
 
Words sentences and dictionaryes by:Diana Villarreal
Words sentences and dictionaryes by:Diana VillarrealWords sentences and dictionaryes by:Diana Villarreal
Words sentences and dictionaryes by:Diana Villarreal
 
Properties of human language
Properties of human language Properties of human language
Properties of human language
 
Word vs lexeme by james jamie 2014 presentation assigned by asifa memon lect...
Word vs lexeme  by james jamie 2014 presentation assigned by asifa memon lect...Word vs lexeme  by james jamie 2014 presentation assigned by asifa memon lect...
Word vs lexeme by james jamie 2014 presentation assigned by asifa memon lect...
 
Systemic Functional Grammar
Systemic Functional Grammar Systemic Functional Grammar
Systemic Functional Grammar
 
Generative grammar
Generative grammarGenerative grammar
Generative grammar
 
Prague school slides
Prague school slidesPrague school slides
Prague school slides
 
Introduction to Suprasegmental Features
Introduction to Suprasegmental FeaturesIntroduction to Suprasegmental Features
Introduction to Suprasegmental Features
 
A Brief Introduction of Morphology
 A Brief Introduction of Morphology A Brief Introduction of Morphology
A Brief Introduction of Morphology
 

En vedette

Semantics Meaning Components
Semantics Meaning ComponentsSemantics Meaning Components
Semantics Meaning ComponentsGrayson Wingate
 
Presentation of text linguistics
Presentation of text linguisticsPresentation of text linguistics
Presentation of text linguisticsali906151
 
Unit 11 Sense Relations (2)
Unit 11   Sense Relations (2)Unit 11   Sense Relations (2)
Unit 11 Sense Relations (2)Ashwag Al Hamid
 
Introduction to linguistics ppt
Introduction to linguistics pptIntroduction to linguistics ppt
Introduction to linguistics pptzouhirgabsi
 
Listening activities
Listening activitiesListening activities
Listening activitiesVũ Cương
 
Sense relations & Semantics
Sense relations & SemanticsSense relations & Semantics
Sense relations & SemanticsAfuza Shara
 

En vedette (10)

Semantics Meaning Components
Semantics Meaning ComponentsSemantics Meaning Components
Semantics Meaning Components
 
Lexical
LexicalLexical
Lexical
 
Ppp3
Ppp3Ppp3
Ppp3
 
Lexicology
LexicologyLexicology
Lexicology
 
Presentation of text linguistics
Presentation of text linguisticsPresentation of text linguistics
Presentation of text linguistics
 
Semantic relation among words
Semantic relation among wordsSemantic relation among words
Semantic relation among words
 
Unit 11 Sense Relations (2)
Unit 11   Sense Relations (2)Unit 11   Sense Relations (2)
Unit 11 Sense Relations (2)
 
Introduction to linguistics ppt
Introduction to linguistics pptIntroduction to linguistics ppt
Introduction to linguistics ppt
 
Listening activities
Listening activitiesListening activities
Listening activities
 
Sense relations & Semantics
Sense relations & SemanticsSense relations & Semantics
Sense relations & Semantics
 

Similaire à 05 linguistic theory meets lexicography

Book review of analyzing grammar an introduction
Book review of analyzing grammar  an introductionBook review of analyzing grammar  an introduction
Book review of analyzing grammar an introductionMehdi ZOUAOUI
 
Natural-Language-Processing-by-Dr-A-Nagesh.pdf
Natural-Language-Processing-by-Dr-A-Nagesh.pdfNatural-Language-Processing-by-Dr-A-Nagesh.pdf
Natural-Language-Processing-by-Dr-A-Nagesh.pdftheboysaiml
 
What can a corpus tell us about grammar
What can a corpus tell us about grammarWhat can a corpus tell us about grammar
What can a corpus tell us about grammarSami Khalil
 
Brand Naming: Linguistic Analysis Terms Defined
Brand Naming: Linguistic Analysis Terms DefinedBrand Naming: Linguistic Analysis Terms Defined
Brand Naming: Linguistic Analysis Terms DefinedBill Smith
 
lesson 1 syntax 2021.pdf
lesson 1 syntax 2021.pdflesson 1 syntax 2021.pdf
lesson 1 syntax 2021.pdfMOHAMEDAADDI
 
06 planning the dictionary
06 planning the dictionary06 planning the dictionary
06 planning the dictionaryDuygu Aşıklar
 
LexicalContrastiveAnalysis. adkdhfjhdfjhd djhfsdhfhfhsd jhsdfsdhksdkfjksd...
LexicalContrastiveAnalysis. adkdhfjhdfjhd    djhfsdhfhfhsd  jhsdfsdhksdkfjksd...LexicalContrastiveAnalysis. adkdhfjhdfjhd    djhfsdhfhfhsd  jhsdfsdhksdkfjksd...
LexicalContrastiveAnalysis. adkdhfjhdfjhd djhfsdhfhfhsd jhsdfsdhksdkfjksd...MonsefJraid
 
328977061-English-Lexicology-2014 2015.pdf
328977061-English-Lexicology-2014 2015.pdf328977061-English-Lexicology-2014 2015.pdf
328977061-English-Lexicology-2014 2015.pdfMaryamAfzal41
 
Linguistics Theories MPB 2014 Progressive-edu.com
Linguistics Theories MPB 2014  Progressive-edu.comLinguistics Theories MPB 2014  Progressive-edu.com
Linguistics Theories MPB 2014 Progressive-edu.comHono Joe
 
Linguistics Theories MPB 2014 Progressive-edu.com
Linguistics Theories MPB 2014  Progressive-edu.comLinguistics Theories MPB 2014  Progressive-edu.com
Linguistics Theories MPB 2014 Progressive-edu.comHono Joe
 
What can a corpus tell us about grammar?
What can a corpus tell us about grammar?What can a corpus tell us about grammar?
What can a corpus tell us about grammar?Pascual Pérez-Paredes
 
Chinese Mandarin Style.pptx
Chinese Mandarin Style.pptxChinese Mandarin Style.pptx
Chinese Mandarin Style.pptxChikoyXhi
 
Presentation of text linguistics
Presentation of text linguisticsPresentation of text linguistics
Presentation of text linguisticsSyed Aitsam Haider
 

Similaire à 05 linguistic theory meets lexicography (20)

Book review of analyzing grammar an introduction
Book review of analyzing grammar  an introductionBook review of analyzing grammar  an introduction
Book review of analyzing grammar an introduction
 
Natural-Language-Processing-by-Dr-A-Nagesh.pdf
Natural-Language-Processing-by-Dr-A-Nagesh.pdfNatural-Language-Processing-by-Dr-A-Nagesh.pdf
Natural-Language-Processing-by-Dr-A-Nagesh.pdf
 
What can a corpus tell us about grammar
What can a corpus tell us about grammarWhat can a corpus tell us about grammar
What can a corpus tell us about grammar
 
Lexicology as a science
Lexicology as a scienceLexicology as a science
Lexicology as a science
 
Brand Naming: Linguistic Analysis Terms Defined
Brand Naming: Linguistic Analysis Terms DefinedBrand Naming: Linguistic Analysis Terms Defined
Brand Naming: Linguistic Analysis Terms Defined
 
lesson 1 syntax 2021.pdf
lesson 1 syntax 2021.pdflesson 1 syntax 2021.pdf
lesson 1 syntax 2021.pdf
 
06 planning the dictionary
06 planning the dictionary06 planning the dictionary
06 planning the dictionary
 
chapter_5_3.pptx
chapter_5_3.pptxchapter_5_3.pptx
chapter_5_3.pptx
 
LexicalContrastiveAnalysis. adkdhfjhdfjhd djhfsdhfhfhsd jhsdfsdhksdkfjksd...
LexicalContrastiveAnalysis. adkdhfjhdfjhd    djhfsdhfhfhsd  jhsdfsdhksdkfjksd...LexicalContrastiveAnalysis. adkdhfjhdfjhd    djhfsdhfhfhsd  jhsdfsdhksdkfjksd...
LexicalContrastiveAnalysis. adkdhfjhdfjhd djhfsdhfhfhsd jhsdfsdhksdkfjksd...
 
328977061-English-Lexicology-2014 2015.pdf
328977061-English-Lexicology-2014 2015.pdf328977061-English-Lexicology-2014 2015.pdf
328977061-English-Lexicology-2014 2015.pdf
 
Linguistics Theories MPB 2014 Progressive-edu.com
Linguistics Theories MPB 2014  Progressive-edu.comLinguistics Theories MPB 2014  Progressive-edu.com
Linguistics Theories MPB 2014 Progressive-edu.com
 
Linguistics Theories MPB 2014 Progressive-edu.com
Linguistics Theories MPB 2014  Progressive-edu.comLinguistics Theories MPB 2014  Progressive-edu.com
Linguistics Theories MPB 2014 Progressive-edu.com
 
What can a corpus tell us about grammar?
What can a corpus tell us about grammar?What can a corpus tell us about grammar?
What can a corpus tell us about grammar?
 
Theory grammar-velyan
Theory grammar-velyanTheory grammar-velyan
Theory grammar-velyan
 
Chinese Mandarin Style.pptx
Chinese Mandarin Style.pptxChinese Mandarin Style.pptx
Chinese Mandarin Style.pptx
 
англ
англангл
англ
 
Presentation of text linguistics
Presentation of text linguisticsPresentation of text linguistics
Presentation of text linguistics
 
MELT 104 Functional Grammar
MELT 104   Functional GrammarMELT 104   Functional Grammar
MELT 104 Functional Grammar
 
Word meaning
Word meaning Word meaning
Word meaning
 
Nlp ambiguity presentation
Nlp ambiguity presentationNlp ambiguity presentation
Nlp ambiguity presentation
 

Dernier

CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)wesley chun
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 

Dernier (20)

CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 

05 linguistic theory meets lexicography

  • 2. Comprehension Questions 1. Write the sense relationships which reflect the similarities between lexical p units. 2. State the kinds of antonyms and explain each of them. 3. Explain ‘frame semantics’ theory. 4. What are the roles of the frames, frame elements and context? 5. Which steps are involved during the analysis process carried out by using frame semantics theory? 6. What is the importance of using the frame semantics approach? 7. Write the information types which are relevant to make a lexicographic record of a word. 8. What are the inherent properties of the headword? 9. Why learning the properties of the source texts is sometimes needed?
  • 3. 5.1 5 1 Preliminaries A grounding in linguistic theory is not a prerequisite for being a proficient lexicographer – still less a guarantee of success i th fi ld l i h till l t f in the field. But there are certain basic linguistic concepts which are invaluable in preparing people to analyse data and to produce concise, accurate dictionary entries. An awareness of linguistic theory can help lexicographers to do their jobs more effectively and with greater confidence. This chapter reviews those linguistic theories which we have found to have direct application to our work as dictionary planners and dictionary makers. 5.2 Sense relationships: similarities This section summarizes different types of ‘similarity’ between lexical units: o Th th t h ti t ti (hyponym and synonymy) d ) Those that share some semantic property or properties (h o Those that denote a part-whole relationship between objects in the real world (meronymy) o Those that allow similar metaphorical sense extensions (regular polysemy) 5.2.1 5 2 1 Hyponymy The nodes of this hierarchy are the ‘superordinate’ and the ‘hyponym’. This relationship can be summarized as ‘if a hyponym then a superordinate’. Its major significance for lexicographers is that the ‘genus expression’ (the central genus expression word or words) in a definition should ideally be the superordinate of the headword. Hyponymy rule of thumb: X is a Y but Y is not only an X (a terrier is a dog).
  • 4. The hyponymy hierarchy is rarely found in adjectives, and consequently there is a real lack of superordinates. Cohyponyms rule of th b X and Y are both Zs ( rose and a tulip are both flowers). C h l f thumb: d b th Z (a d t li b th fl ) 5.2.2 Synonymy Synonyms are words which have the same meaning like ‘pavement’ and ‘sidewalk’. True synonyms are extremely rare; the nearest you get is usually a pseudo-synonymy and l h ll d d synonyms in dictionaries often turn out to be cohyponyms or superordinates. Pure synonymy is rare across languages, except for the names of concrete objects which the two cultures share. Synonymy rule of thumb: X is Y and Y is X (shut is close and close is shut). 5.2.3 Meronymy Meronymy reflects the relationship of the part to the whole and vice versa. It’s difficult to define the part without mentioning the whole but the part is only occasionally referred to in the definition of the whole. Meronymy rule of thumb: X and other parts of Y. Quasi-meronymy reflects the relationship of the member to the group or class of people, or collection of objects. This is a rather loose relationship: it’s difficult to word a formula appropriate to all the cover. varied Lus it should cover Quasi-meronymy rule of thumb: X belongs to / in a Y. 5.2.4 Regular polysemy Some polysemous words have a particular relationship with others i th i ‘l i l s t’ in S l s s ds h ti l l ti shi ith th s in their ‘lexical set’ i that several of their meanings seem to parallel each other.
  • 5. Certain specific semantic components result in sets of words behaving lexicographically in a very similar way. This is known as ‘regular polysemy’. When you re planning the editorial work in a dictionary project it’s obciously a help to you’re project, it s the team if you can list the major instances of regular polysemy, either by producing template entries or simply by issuing lists of headwords related in this way. English morphology encourages a wider range of regular polysemt than is found in languages that have specific forms for verbs and nouns. l h h ifi f f b d 5.3 Sense relationships: differences This section summarizes relationships between LUs that are in some way opposite in h l h b L h meaning. The kinds are complementary, polar and directional antonymy. 5.3.1 5 3 1 Complementary antonymy This relationship is sometimes called ‘contradiction’. Complementary antonymy rule of thumb: If it isn’t X then it must be Y and vice versa. 5 3 2 Polar antonymy 5.3.2 This relationship is similar to, but more complex than, complementarity. There is a gradient between X and Y in polar antonymy. X and Y are at the poles of gradient, area, this gradient but in between there is an indeterminate area where more X and less Y are found. Polar antonymy rule of thumb: If it’s X then it can’t be Y and vice versa, but it can be somewhere in between. 5.3.3 Directional antonymy Directional antonyms include various subtypes: some denote contrary movement or position, for instance, pairs of words representing opposing poles along a shared axis.
  • 6. 5.3.4 Converseness Converseness holds between pairs of words which have a certain semantic symmetry, so that although not antonyms one of the pair is felt in some way to be linked by g y p y y oppositeness to the other. There is little direct application of converse pairs in dictionaries, but if a word is difficult to define a look at its converse’s definition can be helpful. 5.4 Frame semantics The application of this theory to practical lexicography results in the approach to lexicographic relevance which helps lexicographers to identify useful facts in corpus texts. This theory which was produced by Fillmore describes words, their various meanings, and how these are combined with others to form the utterances and sentences of a language. Its aim is to analyse and record for each sense of a word or phrase, the full range of its semantic and syntactic relations. To do this they have devised a suite of codes denoting semantic roles (frame elements) this, and grammatical relationships, which allow them to document in detail the corpus contexts in which a word is found. The work is computer-assisted. The frame semantics approach to word behaviour is the most helpful and appropriate approach to corpus data, ensuring that the analysis is correctly carried out, and no vital fact is overlooked. 5.4.1 5 4 1 What are frames and frame elements Frame semantics describes the meanings of words and phrases in terms of the frame to which they belong and the contexts in which these LUs are found.
  • 7. A semantic frame is a schematic representation of a situation type together with a list of the typical participants, props, and concepts that are to be found in such a situation; these are the semantic roles, or frame elements (Fes). The context is normally the phrase or clause and maximally the sentence in which the target word clause, appears in corpus data. 5.4.2 How is the analysis done? There are several distinct steps in the analysis process: o First, the frame is defined, and its core elements named and described. o Next, a list is made of as many words as can be found which in one of their senses evoke that frame. o Then for each sense or LU a set of corpus sentences is extracted, in which the word is used in Then, sense, LU, extracted the particular sense. o Each sentence is annotated by marking off any section which instantiates an FE and by recording for each FE thus identified: o Its phrase type o Its grammatical function 5.4.3 Why is this useful for lexicographers? The frame semantics approach, grounded in a coherent theory, offers the possibility of a more systematic less subjective way of analysing corpus data and gives us confidence that all relevant systematic, data, features are being captured. 5.5 Lexicographic relevance When looking at the concordances the corpus offers for a word we have to determine ‘what is lexicographically relevant’? We consider lexicographic relevance from the standpoint of Fillmore’s frame semantics.
  • 8. Three types of information are relevant to making a lexicographic record of a word: o What we know, as native speakers, about the headword (its inherent properties) o What we learn from its use in corpora and elsewhere (its contextual features) o What we know about where the citations came from (the properties of the source texts) It’s important to remember that ‘lexicographic relevance’ relates to what is relevant to an LU, and not to a lemma, the focus is the headword in one of its senses, not the whole word. 5.5.1 Inherent properties of the headword This is the knowledge of our language that we all bring to analysing the corpus data and writing the dictionary entry. The properties of the headword that principally concern us can be summarized very briefly: o Its wordclass o Its wordforms o Its grammatical behaviour o Its semantics In corpus lexicography we use our inherent knowledge of the headword rather to help us discover the really useful facts in the corpus, and make sure the entry is comprehensive and h l l i i k the examples are pleasing to our native speakers’’ ears. Our knowledge of the headword’s inherent properties serves as quality control during our work on corpus data, as we discover and record its contextual features in each of its LUs. 5.5.2 Contextual features of the headword An understanding of lexicographic relevance helps you identify in a corpus sentence all the essential components of the headword’s context, all the facts that you need to take into account when writing any entry for that word.
  • 9. 5.5.2.1 Case study: argue The headword argue contains four LUs; each represents a distinct sense of the headword. headword LU 1: the sense of ‘quarrel, dispute’, the communication frame. LU 2: the sense of ‘maintain, make a case for’, the reasoning frame. LU 3: the sense of ‘indicate’, the evidence frame indicate frame. LU 4: the sense of ‘persuade’, the persuasion frame. They will differ for each LU, since the frame elements depend on the frame the LU belongs to. ongs participant 1 participant 2 topic The sentence is ‘Sam / was arguing / with his brother / about the money’. We have to examine its; o Frame elements or semantic roles o Phrase types o Grammatical function Frame elements: Participant 1 Participant 2 Topic Sam with his brother about the money Phrase types + grammatical functions NP: Subject / PP-with: Complement / PP-about: Complement The phrase type information allows you to mark off in the sentence the actual sections relevant to your description. The information about grammatical function lets you assess the importance of the component for your database.
  • 10. The set of threefold descriptions of each component contains most of the information you need to extract from this sentance for your database. Whan we are analysing corpus data in an attempt to collect the facts about a word for our dictionary entry, it’s important to be able to discover from the concordances tha actual source of each citation. This information is stored in the ‘document headers’ of each text in the corpus. Using this information the computer can tell you whether a particular citation comes mainly from spoken or written language, or political documents, or feminist publications and so on. If you h have any d b about the way a word i used, i ’ useful to b able to doubts b h d is d it’s f l be bl check up on where the citation came from. To summarize lexicographic relevance: the wordclass of the word is central to what is relevant to record, and there are lists of the principal co constituents of record co-constituents a clause that are relevant for each of the four major wordclasses.
  • 11. Turkish Summary Bu bölümde sözlük oluşturan kişilerin çalışmalarına katkı sağlayabilecek bazı ş ş ç ş ğ y dilbilimsel kuramlardan ve bu kuramların uygulanış biçimlerinden bahsedilmektedir. Sözcükler arasında birtakım anlamsal ilişkiler vardır ve bu ilişkiler benzerlik ve farklılıklara göre şekillenir. Sözcükler arasındaki benzerlikten doğan ilişkiler sözcüklerin bazı anlambilimsel özellikleri paylaşmalarına nesneler arasındaki paylaşmalarına, parça-bütün ilişkilerine ve sözcüklerin benzer mecazi alt anlamları çağrıştırmalarına göre farklılık gösterir. Sözcükler arasındaki farklılıklardan doğan ilişkiler ise sözcüklerin birbirlerini zıtlıklarla tamamlamalarına, tamamen farklı kavramları çağrıştırmalarına ve birbirlerine zıt olmalarına göre farklılık gösterir. Dilbilimci Fillmore sözlükbilime de uygulanabilen ve ‘yapısal anlambilim’ olarak adlandırılan bir kuram geliştirmiştir. Bu kuram sözcükleri ve onların farklı anlamlarını tasvir eder ve bir dildeki sözce ve tümcelerin oluşturulması için ükl i diğ ükl l l birleştirilmesi gerektiğini açıklar. Bunu yapmak i il i k iği i kl B k sözcüklerin diğer sözcüklerle nasıl bi l için de anlambilimsel rolleri ve dilbilgisel ilişkileri gösteren bazı kodlar tasarlanır. Bu kuramın sözlükbilime uygulanması sonucunda sözlükbilimcilere bütünce metnindeki faydalı bilgileri tanımlama konusunda yardımcı olan sözlükbilimsel ilişki y g y ş yaklaşımı ortaya çıkmıştır. Bir sözcüğün sözlükbilimsel ilişkilerini belirlemek için sözcüğün genel özelliklerinin, bağlamsal özelliklerinin ve kaynak metinlerin özelliklerinin bilinmesi gereklidir.
  • 12. Comprehension Questions / Answers Write the sense relationships which reflect the similarities between lexical units. Different types of ‘similarity’ between lexical units: o Those that share some semantic property or properties (hyponym and synonymy) o Those that denote a part-whole relationship between objects in the real world (meronymy) o Those that allow similar metaphorical sense extensions (regular polysemy) State the kinds of antonyms and explain each of them. The kinds are complementary, polar and directional antonymy. Complementary antonymy This relationship is sometimes called ‘contradiction’. Complementary antonymy rule of thumb: If it isn’t X then it must be Y and vice versa. P l antonymy t Polar This relationship is similar to, but more complex than, complementarity. There is a gradient between X and Y in polar antonymy. X and Y are at the poles of this gra nt, ut n tw n th r s gradient, but in between there is an indeterminate ar a, where more X and less Y ar foun . n t rm nat area, wh r mor an ss are found. Polar antonymy rule of thumb: If it’s X then it can’t be Y and vice versa, but it can be somewhere in between. Directional antonymy Directional antonyms include various subtypes: some denote contrary movement or position, for instance, pairs of words representing opposing poles along a shared axis. Explain ‘frame semantics’ theory.
  • 13. This theory which was produced by Fillmore describes words, their various meanings, and how these are combined with others to form the utterances and sentences of a language. Its aim is to analyse and record for each sense of a word or phrase, the full range of its semantic and syntactic relations. What are the roles of the frames, frame elements and context? A semantic frame is a schematic representation of a situation type together with a list of the typical participants, props, and concepts that are to be found in such a situation; these are the semantic roles, or frame elements (Fes). The context is normally the phrase or clause and roles (Fes) clause, maximally the sentence in which the target word appears in corpus data. Which steps are involved during the analysis process carried out by using frame semantics theory? There are several distinct steps in the analysis process: o First, the frame is defined, and its core elements named and described. o Next, a list is made of as many words as can be found which in one of their senses evoke that f th t frame. o Then, for each sense, or LU, a set of corpus sentences is extracted, in which the word is used in the particular sense. o Each sentence is annotated by marking off any section which instantiates an FE and by y g y y recording for each FE thus identified: o Its phrase type o Its grammatical function What is the importance of using the frame semantics approach? The frame semantics approach, grounded in a coherent theory, offers the possibility of a more systematic, less subjective way of analysing corpus data, and gives us confidence that all relevant features are being captured. Write the information types which are relevant to make a lexicographic record of a word. Three types of information are relevant to making a lexicographic record of a word:
  • 14. o What we know, as native speakers, about the headword (its inherent properties) o What we learn from its use in corpora and elsewhere (its contextual features) o Wh we know about where the citations came from (the properties of the source What k b h h i i f ( h i f h texts) What are the inherent properties of the headword? The properties of the headword that principally concern us can be summarized very briefly: o Its wordclass o Its wordforms ts wor forms o Its grammatical behaviour o Its semantics Why learning the properties of the source texts is sometimes needed? Using this information the computer can tell you whether a particular citation comes mainly from spoken or written language, or political documents, or feminist publications and so on. If you have any doubts about the way a word is used, it’s useful to be able to check up on where the citation came from from.