Introduction to Natural Language
Processing
(aka, Computational Linguistics)
Slides by me, Martha Palmer,
Eleni Miltsakaki, Dan Jurafsky,
Tarkan Kacmaz,
and others
1
Overview
• NLP without linguistics (4-5 weeks)
– Information Retrieval (search)
– Text Classification
– Pattern Matching and Information Extraction
• NLP with sequence structure (~3 weeks)
– HMMs, CRFs
– Sequence labeling tasks
• NLP with more structure (~3 weeks)
– Grammars and parsing
– Learning grammars
– Semantic role labeling
• Selected topics (~2 weeks)
– Learning representations and domain adaptation
– Knowledge-based language processing
2
Practical Matters
• Prereqs: General understanding of
probability and statistics
• Grading:
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20% quizzes and in-class participation
25% Midterm
20% Project
35% Final
• I will supply some ideas for projects later
– Projects to start after the midterm.
– You’re welcome and encouraged to suggest your own
project ideas.
3
WHAT IS LANGUAGE?
When we study human language, we
are approaching what some might call
the “human essence”, the distinctive
qualities of mind that are, so far as we
know, unique to man.
Noam Chomsky
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 phonetics?
•
•
•
•
•
Phonetics is the science of speech.
We all speak.
But how many of us know how we speak?
Or what speech is like?
Phonetics seeks to answer those
questions.
Orthography and Sounds
• The English language is not phonetic.
• Words are not spelled as they are
pronounced
• There is no one-to-one correspondence
between the letters and the sounds or
phonemes.
Orthography and Sounds
• Did he believe that Caesar could see
the people seize the seas.
• The silly amoeba stole the key to the
machine
Articulatory Phonetics
• The production of any speech sound
involves the movement of an air stream.
• Most speech sounds are produced by
pushing the air out of the lungs through
the mouth (oral) and sometimes through
the nose (nasal).
SPEECH ORGANS
Phonology
• Phonology deals with the system and
pattern of speech sounds in a language.
• Phonology of a language is the
system and pattern of speech sounds.
Phonology
Phonological knowledge permits us to:
•
•
•
•
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produce sounds which form meaningful utterances,
to recognize a “foreign” accent,
to make up new words,
To know what is or is not a sound in one’s language
to know what different sound strings may represent
Phonetics vs Phonology
Phonetics
The study of speech
sounds.
Phonology
The study of the way
speech sounds form
patterns.
Sequences of Phonemes
k
blık
klıb
bılk
kılb
b
possible
l
ı
Ibkı
ılbk
bkıl
ıblk
•“I just bought a beautiful new blick” What is a blick?
•“I just bought a beautiful new bkli” WHAT!!
impossible
Sequences of Phonemes
• Your knowledge of English “tells” you that
certain strings of phonemes are permissible
and others are not.
• That’s why /bkli/ does not sound like an
English word.
• It violates the restrictions on the sequencing of
phonemes; i.e. it violates the phonological
rules of English.
Rules of Phonology
• Delete a word-final /b/ when it occurs
after a /m/
as in:
But not!
bomb
crumb
lamb
tomb
bombard
crumble
limber
tumble
Morphology & Syntax
• Morphology deals with the combination
of morphemes into words.
• Syntax deals with the combination of
words into sentences.
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)
• Open + ed = opened
• Open + ing = opening
– Derivational (e.g. adverbs from adjectives, nouns
from adjectives)
• Happy  happily
• Happy  happiness (nouns from adjectives)
32
Syntax
The study of classes of words
and the rules that govern how the words can
combine to make phrases and sentences.
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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
– Articles, pronouns, prepositions, particles, quantifiers,
conjunctions
34
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
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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
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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
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“Complements”
• Notice that to be meaningful the verb “go”, for
example requires a phrase for “location”
– *John went
– John went home
• Such phrases “complete” the meaning of the
verb (or other type of head) and are called
complements
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Inside the noun phrase
• NPs are used to refer to things: objects, places,
concepts, events, qualities, etc
• NPs may consist of:
–
–
–
–
–
A single pronoun (he, she, etc)
A name or proper noun (John, Athens, etc)
A specifier and a noun
A qualifier and a noun
A specifier and a qualifier and a noun (e.g., the first
three winners)
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Specifiers
• Specifiers indicate how many objects are
described and also how these objects
relate to the speaker
• Basis types of specifiers
– Ordinals (e.g., first, second)
– Cardinals (e.g., one, two)
– Determiners (see next slide)
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Determiners
• Basic types of determiners
– Articles (the, a, an)
– Demonstratives (this, that, these, those)
– Possessives (‘s, her, my, whose, etc)
– Wh-determiners (which, what –in questions)
– Quantifying determiners (some, every, most,
no, any, etc.)
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Qualifiers
• Basic types of qualifiers
– Adjectives
• Happy cat
• Angry feelings
– Noun modifiers
• Cook book
• University hospitals
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Inside the verb phrase
• A simple VP
– Adverbial modifier + head verb +
complements
• Types of verbs
– Auxiliary (be, do, have)
– Modal (will, can, could)
– Main (eat, work, think)
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Types of verb complements
• Intransitive verbs do not require complements
• Transitive verbs require an object as a complement (e.g.
find a key)
• Transitive verbs allow passive forms (e.g. a key was
found)
• Ditransitive verbs require one direct and on indirect
object (e.g. give Mary a book)
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Other verb complements
• Clausal complements
– Some verbs require clausal complements
• Mary knows that John left
• Prepositional phrase complements
– Some verbs requires specific PP complements
• Mary gave the book to John
– Others require any PP complement
• John put the book on the shelf/in the room/under the table
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Adjective phrases
• Simple
– Angry, easy, etc
• Complex
– Pleased with the prize
– Angry at the committee
– Willing to read the book
• Complex AdjP normally do not precede nouns, they are
used as complements of verbs such as be or seem
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Adverbial phrases
• Indicators of
–
–
–
–
–
–
Degree
Location
Manner
The time of something (now, yesterday, etc)
Frequency
Duration
• Location in the sentence
– Initial
– Medial
– Final
47
Grammars and parsing
• What is syntactic parsing
– Determining the syntactic structure of a
sentence
• Basic steps
– Identify sentence boundaries
– Identify what part of speech is each word
– Identify syntactic relations
48
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
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NP
Det
the
N
mat
Parses
Time flies like an arrow.
S
NP
VP
N
time
V
flies
PP
Prep
like
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NP
Det
an
N
arrow
Parses
Time flies like an arrow.
S
NP
N
time
N
flies
VP
V
like
NP
Det
an
52
N
arrow
Features
• C for Case, Subjective/Objective
– She visited her.
• P for Person agreement, (1st, 2nd, 3rd)
– I like him, You like him, He likes him,
• N for Number agreement, Subject/Verb
– He likes him, They like him.
• G for Gender agreement, Subject/Verb
– English, reflexive pronouns He washed himself.
– Romance languages, det/noun
• T for Tense,
– auxiliaries, sentential complements, etc.
– * will finished is bad
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Semantics and Pragmatics
High-level Linguistics (the good stuff!)
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)
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Language to Logic
• John went to the book store.
 John  store1, go(John, store1)
• John bought a book.
buy(John,book1)
• John gave the book to Mary.
give(John,book1,Mary)
• Mary put the book on the table.
put(Mary,book1,table1)
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Semantics
Same event - different sentences
John broke the window with a hammer.
John broke the window with the crack.
The hammer broke the window.
The window broke.
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Same event - different syntactic frames
John broke the window with a hammer.
SUBJ VERB
OBJ
MODIFIER
John broke the window with the crack.
SUBJ VERB
OBJ
MODIFIER
The hammer broke the window.
SUBJ VERB
OBJ
The window broke.
SUBJ VERB
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Semantics -predicate arguments
break(AGENT, INSTRUMENT, PATIENT)
AGENT
PATIENT
INSTRUMENT
John broke the window with a hammer.
INSTRUMENT
PATIENT
The hammer broke the window.
PATIENT
The window broke.
Fillmore 68 - The case for case
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AGENT
PATIENT
INSTRUMENT
John broke the window with a hammer.
SUBJ
OBJ
MODIFIER
INSTRUMENT
PATIENT
The hammer broke the window.
SUBJ
OBJ
PATIENT
The window broke.
SUBJ
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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
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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
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Natural Language Processing
Applications and Tasks
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•
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Machine Translation
Question-Answering
Information Retrieval
Information Extraction
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Machine Translation
• One of the first applications for computers
– bilingual dictionary > word-word translation
• Good translation requires understanding!
– War and Peace, The Sound and The Fury?
• What can we do? Sublanguages.
– technical domains, static vocabulary
– Meteo in Canada, Caterpillar Tractor
Manuals, Botanical descriptions, Military
Messages
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Example translation
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Machine Translation
• Chinese gloss: Dai-yu alone on bed top think-of-with-gratitude Baochai again listen to window outside bamboo tip plantain leaf of ontop rain sound sigh drop clear cold penetrate curtain not feeling
again fall down tears come
• Hawkes translation: As she lay there alone, Dai-yu’s thoughts turned
to Bao-chai… Then she listened to the insistent rustle of the rain on
the bamboos and plantains outside her window. The coldness
penetrated the curtains of her bed. Almost without noticing it she
had begun to cry.
Machine Translation
• The Story of the Stone
– =The Dream of the Red Chamber (Cao Xueqin 1792)
• Issues: (“Language Divergences”)
– Sentence segmentation
– Zero-anaphora
– Coding of tense/aspect
– Penetrate -> penetrated
– Stylistic differences across languages
• Bamboo tip plaintain leaf -> bamboos and plantains
– Cultural knowledge
• Curtain -> curtains of her bed
Question Answering
• What does “archaeopteryx” mean?
• What year was Abraham Lincoln born?
• How many states were in the United
States when Lincoln was born?
• Was there a military draft during the
Hoover administration?
• What do philosophers think about whether
human cloning should be legal?
Modern QA systems
• Still in infancy
• Simple factoid questions beginning to work
OK
• Annual government-sponsored “bakeoff”
called TREC
Issues in NLP
• Ambiguity
• World Knowledge – it’s needed for
understanding, but computers don’t have it
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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
Modern conversational agents
• Switchboard Receptionists
– Implications: need to know how a native or non-native speaker of
English is likely to pronounce a random American name. Eek.
• Airline and other simple dialogue systems
– Lots of fabulously fun pragmatic issues
• Grounding
• Error handling
• In general
– Now that there are commercial installations
– Big incentive to use linguistic or any other kind of knowledge if it
actually improves performance
Eliza: Weizenbaum (1966)
• User: You are like my father in some ways.
• ELIZA: What resemblance do you see
• User: You are not very aggressive but I think you don’t want me to
notice that.
• ELIZA: What makes you think I am not aggressive
• User: You don’t argue with me
• ELIZA: Why do you think I don’t argue with you
• User: You are afraid of me
• ELIZA: Does it please you to believe I am afraid of you