Introduction to
Natural Language Processing
A.k.a., “Computational Linguistics”
Recall: Agents and Environment
Environment
Agent
sensors
percepts
?
actuators
actions
Agents and Environments with NLP
Agent
1.
2.
sensors
What do the other agents
claim to believe?
(NL Understanding)
What do the other agents
actually believe or want?
Environment
Speech,
Handwriting, Agent
printed text,
Agent
digital text
Agent
(Plan recognition, game theory)
3.
How can I make the other
agents believe X?
(Planning, NL Generation)
actuators
Speech,
Handwriting,
printed text,
digital text
WHAT IS LANGUAGE?
• Definition with respect to form:
Language is a system of speech symbols. It is realized
acoustically (sound waves), visually-spatially (sign language)
and in written form.
• Definition with respect to function:
Language is the most important means of human
communication. It is used to convey and exchange
information (informative function)
• Multiplicity of languages:
We know of about 7000 languages, which is estimated
to be about 1% of all the languages that ever existed.
LANGUAGE AND THE BRAIN
LANGUAGE AND THE BRAIN
THEORIES OF LANGUAGE
• Noam Chomsky claims that language is innate.
• B. F. Skinner claims that language is learned; it is basically a
stimulus-response mechanism.
WHAT IS GRAMMAR?
• When we learn a language we also learn the rules that
govern how language elements, such as words, are combined
to produce meaningful language.
• These elements and rules constitute the Grammar of a
language.
• The Grammar is “what we know”
• Grammar represents our linguistic competence.
DESCRIPTIVE vs PRESCRIPTIVE
GRAMMAR
Prescriptive
(should be)
Descriptive
(is)
Areas of Linguistics
• phonetics - the study of speech sounds
• phonology - the study of sound systems
• morphology- the rules of word formation
• syntax - the rules of sentence formation
• semantics - the study of word meanings
• pragmatics – the study of discourse meanings
• sociolinguistics - the study of language in society
• applied linguistics –the application of the methods and
results of linguistics to such areas as language teaching,
national language policies, lexicography, translation, language
in politics etc.
What is the meaning of ‘meaning’?
• Learning a language includes learning the
“agreed upon” meanings of certain strings
of sounds and,
• Learning how to combine these meaningful
units into larger units which also convey
meaning.
Morphemes
• Morpheme is the smallest linguistic unit
that has meaning.
• Morpheme is a grammatical unit in which
there is an arbitrary union of sound and a
meaning and,
• which cannot be further analysed (broken
down into parts that have meaning).
Morphemes
• A morpheme may be represented by a
single sound:
• e.g. the plural morpheme [s] in cat+s
• A morpheme may be represented by a
syllable (monosyllabic):
• e.g. child+ish
Morphemes
A morpheme may be represented by more than
one syllable (polysyllabic):
• e.g. lady, water
or three syllables:
• e.g. crocodile
or four syllables:
• e.g. salamander
Words
• Two basic ways to form words
– Inflectional (e.g. English verbs + endings  other English
verbs)
• Open + ed = opened
• Open + ing = opening
– Derivational (e.g. adverbs from adjectives, nouns from
adjectives)
• Happy  happily
• Happy  happiness (nouns from adjectives)
15
Syntax
The study of classes of words (nouns, verbs, etc.)
and the rules that govern how the words can combine
to make phrases and sentences.
16
Basic classes of words
• Classes of words aka parts of speech (POS)
–
–
–
–
Nouns
Verbs
Adjectives
Adverbs
• The above classes of word belong to the type open class
words
• We also have closed class words, or function words
– Articles, pronouns, prepositions, particles, quantifiers, conjunctions
17
Basic phrases
• A word from an open class can be used to
form the basis of a phrase
• The basis of a phrase is called the head
18
Examples of phrases
• Noun phrases
– The manager of the institute
– Her worry to pass the exams
– Several students from the English Department
• Adjective phrases
– easy to understand
– mad as a dog
– glad that he passed the exam
19
Examples of phrases
• Adverb phrases
– fast like the wind
– outside the building
• Verb phrases
– ate her sandwich
– went to the doctor
– believed what I told him
20
Grammars and parsing
• syntactic parsing:
Determining the syntactic structure of a sentence
• Basic steps
– Identify sentence boundaries
– Identify what part of speech is each word
– Identify pairs of words that form phrases
– Identify pairs of phrases that form larger phrases
…
21
Context Free Grammar
•
•
•
•
•
•
•
•
S -> NP VP
NP -> det (adj) N
NP -> Proper N
NP -> N
VP -> V, VP -> V PP
VP -> V NP
VP -> V NP PP, PP -> Prep NP
VP -> V NP NP
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Parses
The cat sat on the mat
S
NP
VP
Det
the
N
cat
PP
V
sat
Prep
on
NP
Det
the
N
mat
23
Parses
Time flies like an arrow.
S
NP
VP
N
time
V
flies
PP
Prep
like
NP
Det
an
N
arrow
24
Parses
Time flies like an arrow.
S
NP
N
time
N
flies
VP
V
like
NP
Det
an
N
arrow
25
Semantics and Pragmatics
Semantics: the study of meaning that can be
determined from a sentence, phrase or word.
Pragmatics: the study of meaning, as it depends
on context (speaker, situation)
26
Language to Logic
• John went to a book store.
s . bookstore(s) ^ go(John, s)
• Every boy loves a girl.
∀b . boy(b)  ∃g . girl(g) ^ loves(b, g)
• Who broke the vase?
λx . broke(x, vase17)
27
Headlines
• Police Begin Campaign To Run Down Jaywalkers
• Iraqi Head Seeks Arms
• Teacher Strikes Idle Kids
• Miners Refuse To Work After Death
• Juvenile Court To Try Shooting Defendant
28
Language Families
NLP tends to focus on:
• Syntax
– Grammars, parsers, parse trees, dependency
structures
• Semantics
– Subcategorization frames, semantic classes,
ontologies, formal semantics
• Pragmatics
– Pronouns, reference resolution, discourse
models
30
Issues in NLP
• Ambiguity
• Lack of Knowledge – it’s needed for
understanding, but computers don’t have it
31
Ambiguity
• Computational linguists are obsessed with
ambiguity
• Ambiguity is a fundamental problem of
computational linguistics
• Resolving ambiguity is a crucial goal
Ambiguity
• Find at least 5 meanings of this sentence:
– I made her duck
Ambiguity
• Find at least 5 meanings of this sentence:
– I made her duck
•
•
•
•
•
•
I cooked waterfowl for her benefit (to eat)
I cooked waterfowl belonging to her
I created the (plaster?) duck she owns
I caused her to quickly lower her head or body
I waved my magic wand and turned her into undifferentiated waterfowl
At least one other meaning that’s inappropriate for gentle company.
Ambiguity is Pervasive
• I caused her to quickly lower her head or body
– Lexical category: “duck” can be a N or V
• I cooked waterfowl belonging to her.
– Lexical category: “her” can be a possessive (“of her”) or dative (“for
her”) pronoun
• I made the (plaster) duck statue she owns
– Lexical Semantics: “make” can mean “create” or “cook”
Ambiguity is Pervasive
• Grammar: Make can be:
– Transitive: (verb has a noun direct object)
• I cooked [waterfowl belonging to her]
– Ditransitive: (verb has 2 noun objects)
• I made [her] (into) [undifferentiated waterfowl]
– Action-transitive (verb has a direct object and
another verb)
– I caused [her] [to move her body]
Ambiguity is Pervasive
• Phonetics!
–
–
–
–
–
–
–
–
–
–
I mate or duck
I’m eight or duck
Eye maid; her duck
Aye mate, her duck
I maid her duck
I’m aid her duck
I mate her duck
I’m ate her duck
I’m ate or duck
I mate or duck
Kinds of knowledge needed?
• Consider the following interaction with
HAL the computer from 2001: A Space
Odyssey
• Dave: Open the pod bay doors, Hal.
• HAL: I’m sorry Dave, I’m afraid I can’t do
that.
Knowledge needed to build HAL?
• Speech recognition and synthesis
– Dictionaries (how words are pronounced)
– Phonetics (how to recognize/produce each sound of English)
• Natural language understanding
– Knowledge of the English words involved
• What they mean
• How they combine (what is a `pod bay door’?)
– Knowledge of syntactic structure
• I’m I do, Sorry that afraid Dave I’m can’t
What’s needed?
• Dialog and pragmatic knowledge
– “open the door” is a REQUEST (as opposed to a
STATEMENT or information-question)
– It is polite to respond, even if you’re planning to
kill someone.
– It is polite to pretend to want to be cooperative
(I’m afraid I can’t…)
– What is `that’ in `I can’t do that’?
• Even a system to book airline flights needs
much of this kind of knowledge
Computational models of how natural
languages work
These are sometimes called Language Models
or sometimes Grammars
Three main types (among many others):
1. Document models, or “topic” models
2. Sequence models: Markov models, HMMs,
others
3. Context-free grammar models
Computational models of how natural
languages work
Most of the models I will show you are
- Probabilistic models
- Graphical models
- Generative models
In other words, they are essentially Bayes Nets.
In addition, many (but not all) are
- Latent variable models
This means that some variables in the model are not
observed in data, and must be inferred.
(Like the hidden states in an HMM.)