Word Meaning and Concepts Flashcards
Components of Comprehension
Identify words
• Retrieve:
– Syntactic class of words
– Word meaning (and related conceptual information)
• Interpret sentence structure (syntax)
• Interpret and link constituent idea units (propositions)
• Build a mental model of the text as a whole
• Interpret the meaning of the speaker/writer
THE LEXICON
• The “mental dictionary” • Contains information about: – The sound of a word (phonology) – Its meaning (semantics) – How it is written (orthography) – How it can be used (syntactic role/part of speech).
WHY DO WE HAVE CONCEPTS?
Cognitive economy and prediction:
• Concepts enable us to generalise from past experiences to a new
instance.
• Categorisation predicts
– provided you generalise on the right basis
• Conceptual hierarchies provide economy of representation
– decreases the amount of information (that needs to be
perceived, remembered and recognised).
MAJOR TYPES OF “PHYSICAL
OBJECT” CONCEPT
- NATURAL KIND TERMS
– Things that exist in the natural world: types of
animal, plant etc.
• e.g. dog, rose, water
• 2. ARTEFACTS
– Things people have made to serve a particular
function, and which are therefore defined in terms
of their ability to fulfil that function.
– e.g. chair, car, pencil
WHAT IS A CONCEPT?
The “Classical” view:
– There are necessary and sufficient conditions for class
membership (e.g. semantic networks, feature models).
• The “Prototype” view:
– Things that are more or less like a prototypical member
• The “Theory” view:
– A theoretically-based method of linking a set of things
together
HIERARCHICAL NETWORK MODEL
e.g. Collins & Quillian (1969)
The semantic distance effect – Canaries have skin > – Canaries have feathers > – Canaries can sing • Retrieval time determined by number of links through which activation must spread
HIERARCHICAL MODEL:
PROBLEMS
Verification times also influenced by:
– When concepts are acquired
RT for “a dog is an animal”
FEATURE MODELS
e.g. Smith, Shoben and Rips (1974)
The meaning of a word is represented as a set of
features.
• These are bivalent, e.g. +ANIMATE
• More specific concepts have more features than
do general ones.
e.g. POODLE has all the DOG features, plus
others specific to poodles.
THE CLASSICAL VIEW (Aristotle)
Holds that the meaning of a concept can be expressed as the set of
attributes that define the concept.
– E.g. a bachelor is ‘unmarried’, ‘male’, ‘adult’.
• These attributes are:
• Singly necessary (essential)
– not merely frequently associated with being a member
• having four sides: necessary for square
• A set of such features is jointly sufficient
– a closed figure, four sides, sides of equal length, and equal angles
• jointly sufficient for square (size, colour, etc. are irrelevant)
• Fits with hierarchical structure of concepts
– apples share a set of defining features with other members of the superordinate
category fruit
– differ from pears, bananas, etc. in terms of other defining features
THE CLASSICAL VIEW: Important Assumptions
- Concepts have defining features.
- Arbitrariness assumption: features are associated with
concepts in an arbitrary way. - All-or-none assumption: instances either are or are
not members of a category.
PROBLEMS WITH THE
CLASSICAL VIEW
- CONCEPTS DO NOT HAVE DEFINING FEATURES
• Hard to give clear cut definitions (the defining features should
provide these). E.g. hard to find necessary and sufficient
features for the concept: games
– Wittgenstein’s notion of family resemblance
• For superordinate concepts, rather than “basic-level” concepts it
is hard to come up with defining features - e.g. furniture (cf.
chair vs. clock) - CONCEPTS ARE NOT ARBITRARY3. CONCEPTS ARE NOT ‘ALL-OR-NONE’
TYPICALITY EFFECT
time to say that instances are exemplars of a category
THE PROBABILISITIC VIEW
main version: Prototypes
There are no defining features, only characteristic
ones.
• A concept is represented as a summary set of the
features typical of the concept: an example, or ideal,
that possesses all the features.
• Rosch and Mervis (1975) showed that good exemplars
(prototypes) have large number of features in common,
poor exemplars have few.
Explains typicality effects: Typical instances are
classified more rapidly because they are more
similar to the prototype.
• Explains lack of clear boundaries between
concepts.
PROBLEMS WITH THE PROBABILISTIC VIEW
- PROBLEMS WITH TYPICALITY EFFECTS
Armstrong, Gleitman & Gleitman (1983) used well-defined
concepts like ‘odd number’.
They found that some instances (7,13) were rated more
typical than others (23, 193), and people were faster to judge
those rated more typical. - CONCEPTUAL COMBINATION
How to combine the prototypes for fish and pet to get pet fish? - PROBLEMS WITH FEATURE SIMILARITY
a. What counts as an attribute.
b. Concepts are not just the sum of constituent
attributes.
THE “THEORY” THEORY
Murphy (1989): stressed importance of person’
s
intuitive model of the social and physical world -
something like a set of schemas.
• People have theories about categories and why they
cohere and sets of beliefs about what makes instances
members of categories
