Syntax and semantics

Rushdi Shams, Dept of CSE, KUET, Bangladesh 1
Syntax and SemanticsSyntax and Semantics
Artificial IntelligenceArtificial Intelligence
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Part IPart I
SyntaxSyntax

Introduction
Natural Language means any language we speak
Natural Language Processing (NLP) means processing the
language in concern so that it can be represented in
machine readable format
Languages consist of grammar
If grammar is not understood by you, how can you develop
NLP systems that can read (parse) sentences, recognize
every word, their Part of Speech (POS)?
How can you represent knowledge from a sentence with a
knowledge representation software if you yourself do not
understand the way language is formed?

Components of a Language
 There are three components of a language-
1. Lexicon
2. Categorization
3. Grammar Rules

Lexicon
stench | breeze | glitter | nothing | wumpus | pit | pits | gold | east |stench | breeze | glitter | nothing | wumpus | pit | pits | gold | east | ....
is | see | smell | shoot | feel | stinks | go | grab | carry | kill | turn |is | see | smell | shoot | feel | stinks | go | grab | carry | kill | turn | ……
right | left | east | south | back | smelly |right | left | east | south | back | smelly | ……
here | there | nearby | ahead | right | left | east | south | back |here | there | nearby | ahead | right | left | east | south | back | ……
me | you | I | it | S=HEme | you | I | it | S=HE || Y’ALLY’ALL ……
John | Mary | Boston | UCB | PAJC |John | Mary | Boston | UCB | PAJC | ……
the | a | an |the | a | an | ……
to | in | on | near |to | in | on | near | ……
and | or | but |and | or | but | ……
0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 90 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9

Categorization
NounNoun >>stench | breeze | glitter | nothing | wumpus | pit | pits | gold | east |stench | breeze | glitter | nothing | wumpus | pit | pits | gold | east | ....
VerbVerb >>is | see | smell | shoot | feel | stinks | go | grab | carry | kill | turn |is | see | smell | shoot | feel | stinks | go | grab | carry | kill | turn | ……
AdjectiveAdjective >>right | left | east | south | back | smelly |right | left | east | south | back | smelly | ……
AdverbAdverb >>here | there | nearby | ahead | right | left | east | south | back |here | there | nearby | ahead | right | left | east | south | back | ……
PronounPronoun >>me | you | I | it | S=HEme | you | I | it | S=HE || Y’ALLY’ALL ……
NameName >>John | Mary | Boston | UCB | PAJC |John | Mary | Boston | UCB | PAJC | ……
ArticleArticle >>the | a | an |the | a | an | ……
PrepositionPreposition >> to | in | on | near |to | in | on | near | ……
ConjunctionConjunction >>and | or | but |and | or | but | ……
DigitDigit >>0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 90 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9

Grammar Structure
In this lecture and the one following it, attending it
carefully does not mean you know all of English
language
Because, that will take you to read NLP as one subject
for 4 years! 
We will learn how to define the basic grammar
structure for NLP systems
We will also learn what things you need to keep in
your head while devising such systems

Syntactic Tree
Human recognizes the organization of words
according to their POS in a sentence with trees.
Are you denying?
Well you can. Because, you didn’t learn it this way in
your childhood.
No one did!
But it has been proved that our brain draws a tree like
structure when we first develop our skills on language
That research is beyond this lecture

Syntactic Tree
So, if you really do that unintentionally, then why not
learn it on pen and paper so that you can understand
how you will teach machines to learn languages?
The tree structure human contemplates is called
syntactic tree

Parsing a Syntactic Tree
Parsing is the process of using grammar rules to
determine whether a sentence is legal, and to obtain
its syntactical structure
‘The large cat eats the small rat’

The large cat eats the small rat
Parsing

The large cat
Article adjective noun
eats the small rat
Parsing
Verb

The large cat
Article adjective noun noun phrase
eats the small rat
Parsing
Verb

The large cat
Article adjective noun Verb noun phrase
Noun phrase
eats the small rat
Parsing

The large cat
Noun phrase verb phrase
eats the small rat
Parsing

The large cat
Noun phrase verb phrase
sentence
eats the small rat
Parsing

Syntactic Tree
The point where lines begin or end is called node
Each node has labels like S, PP or chased
If 2 nodes are connected by a line, the upper node is immediate
dominator of the lower node. D is the immediate dominator of the
Upper nodes in a branch are called dominators. NP is the dominator
of D, N, the, dog

Syntactic Tree
Two nodes are sisters if they are immediately dominated by
same node. D and N are sisters.
The immediate dominator of them is called their mother. NP is
the mother of D and N. Similarly, D and N are daughters of NP
The dominators of them are called their parents

Syntactic Tree
Constituents are the terminal nodes that are all
dominated by a single non-terminal node. Chased a
cat into the garden are constituents as they are
dominated by VP

Label Bracketing
It is a process of representing
the syntactic tree in another
way.

Do yourself: Label Bracket the tree

Remember, you may have to practise the reverse-
constructing a syntactic tree from label
bracketing 

Constituents and Categories
 Tree structure provides two information-
1. It divides the sentence into constituents (in
English, these are called phrases)
2. It puts them into categories (NP, VP, etc)

 How do we know what would be the right way to group
words into right category?
 How do we know into the garden is a category, but a cat
into is not?
 Any words that can be moved as group are probably
constituents- the meaning of the dog chased a cat into
the garden and into the garden, the dog chased a cat.
 Which one did you move? Into the garden- right?
 And the meaning did not change
 That’s probably our constituent

 Any string of words that can be deleted is
probably a constituent
 If you omit into the garden from the sentence,
nothing is changed grammatically.
 Usually, meaning of unit of words makes sense.
Into the garden is much more meaningful than a
cat into

 However, we are only talking about syntactic
structure, not the semantic one.
 The dog, the cat and the garden- their grammar
structure is saying they are all noun phrases.
 It means, they can be used interchangeably- no
linguist can deny that
 Then what about- “The garden chased the cat
into the dog”? 
 We will not focus on semantics, said you before!

Ambiguity
There are 2 types of ambiguity-
1. Lexical Ambiguity: Sentence contains an
idiom/word/term that has more than one meaning.
Glasses means both drinking glasses and spectacles
2. Structural Ambiguity: Sentence has more than one
syntactic tree
I saw the boy with the telescope-
Did you see the boy with a telescope? Or
Did you see the boy who was having a telescope?

Structural Ambiguity

Ambiguity
 Which of the following examples have lexical
ambiguity and which of them carry structural
ambiguity; justify-
1. The painter put on another coat
2. We like flying planes
3. The judge threw the book at him
4. Visiting relatives can be tiresome

Ambiguity
Da Vinci liked to paint his models nude.
He wrote the note yesterday
You mean you carried the information by a bus?
Connecting wires are tiring in DLD lab
Squad helps dog bite victim

Now, We will take a look at How
to Construct Grammar

Noun Phrase
We will start with a Noun Phrase (NP)
At a first glance, we can say, an NP can be as of-
NP -> D (Adj) N (PP)
the dog -> D N
the gray cat -> D Adj N
the dog in the garden -> D N PP
the young boy with the telescope -> D Adj N PP
p.s. ( ) means optional presence

Determiner
Determiners can be NULL as in-
Birds fly
So, for the rule
NP -> D (Adj) N (PP)
we can say that D - > NULL or
D-> A, An, The
p.s. for simplicity, we are not taking the two as
determiner here, in spite of its eligibility of being so

Noun Phrase (continued)
NPs can be simply pronouns
NP -> Pronoun
NPs can be simply nouns as well
NP -> Names
And Pronouns and Names are then-
Pronoun -> he, she, we, you, they, I
Names -> Mehedi, Shams, Rushdi

Adjectives
It is permitted in English to put one million adjectives in front
of nouns.
Therefore, our rule for noun phrase
NP -> D (Adj) N (PP)
will face problems for-

Adjectives
No problem! We can change the rule as follows-
That will help us with a recursion like-

Adjective Phrase
An adjective is not always a single word
It can be a phrase as in-
So, in that case, we need to change the rule slightly-

Sentences within NPs
In NPs such as the fact that birds fly, there is a
sentence after the complementizer- that
So, we need to change the rule as-
And we also need rules as follows to satisfy such NPs-

So, our rules so far…

Parsing
Now, with these rules inside your lexicon, we will see,
how machine parses top down and bottom up for the
sentence-
The fact that birds fly surprised him

Difficulties with Natural Language:
Anaphora
Using pronouns to refer back to entities alreadyUsing pronouns to refer back to entities already
introduced in the textintroduced in the text
After Mary proposed to John,After Mary proposed to John, theythey found a preacherfound a preacher
and got married.and got married.
For the honeymoon,For the honeymoon, theythey went to Hawaiiwent to Hawaii
Mary saw a ring through the window and asked JohnMary saw a ring through the window and asked John
forfor itit
Mary threw a rock at the window and brokeMary threw a rock at the window and broke itit

Indexicality
Indexical sentences refer to utterance situationIndexical sentences refer to utterance situation
(place, time, etc.)(place, time, etc.)
I am overI am over herehere
Why did you doWhy did you do thatthat??

Metonymy
Using one noun phrase to stand for anotherUsing one noun phrase to stand for another
I've readI've read ShakespeareShakespeare
ChryslerChrysler announced record profitsannounced record profits
TheThe ham sandwichham sandwich on Table 4 wants another beeron Table 4 wants another beer

Metaphor
““Non-literal" usage of words and phrases, oftenNon-literal" usage of words and phrases, often
systematic.systematic.
I've tried killing the process but it won't die. Its parentI've tried killing the process but it won't die. Its parent
keeps it alive.keeps it alive.

Reference
NLP for Prolog Programmers by Michael A.
Covington
Chapter 4

Part IIPart II
SemanticsSemantics

Structure of Language
Words
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………
Sentences
(Phrases)
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Discourse
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Syntax
Pragmatics
semantics

Semantics in NL
I can't untie that knot with one hand.
The sentence is about the abilities of whoever spoke
or wrote it. (Call this person the speaker.)
It's also about a knot, maybe one that the speaker is
pointing at
The sentence denies that the speaker has a certain
ability. (This is the contribution of the word `can't'.)
Untying is a way of making something not tied.
The sentence doesn't mean that the knot has one
hand; it has to do with how many hands are used to do
the untying.

Problems in Semantics in NL
If you do not understand certain characteristics of
linguistics, you will not be able to understand the
semantics.
If you do understand them, you need to feel them
If you do feel them, you need to see the context
If you see the context, you are dealt with both
semantics and pragmatics in NL


Synonymy
Synonyms are different words (or sometimes
phrases) with identical or very similar meanings.
Words that are synonyms are said to
be synonymous, and the state of being a synonym
is called synonymy

Synonymy
student and pupil (noun)
buy and purchase (verb)
sick and ill (adjective)
quickly and speedily (adverb)
on and upon (preposition)

Synonymy
Note that synonyms are defined with respect to
certain senses of words
pupil as the "aperture in the iris of the eye" is not
synonymous with student.
Similarly,he expired means the same as he died,
yet my passport has expired cannot be replaced
by my passport has died.

Antonymy
Antonyms are words with opposite or nearly
opposite meanings. For example:
short and tall
dead and alive
increase and decrease

Homonymy
a homonym is one of a group of words that
share the same spelling and
the same pronunciation but
have different meanings, usually as a result of the two
words having different origins.
The state of being a homonym is called homonymy.
bark (the sound of a dog) and bark (the skin of a
tree).

Heteronymy
heteronyms (also known as heterophones) are
words with
identical spellings (or characters)
but different pronunciations and meanings.

Semantic Features
Nouns can be classified according to the values of a
set of semantic features.
For example, the word boy can be paraphrased as
young male human, man as not-young male human.
The difference in meaning between boy and man
seems reside in the value of age.

Semantic Features
Thus we could take AGE to be a primitive, here taking
the values young and not-young.
Boy is defined by
AGE = young (among other features), man by AGE =
not-young.

Semantic Features
 Some more general semantic features which are have been used for nouns
include:
1. ABSTRACT Nouns with the feature +ABSTRACT are abstract or non-concrete (e.g.
sincerity), those with the feature –ABSTRACT are concrete (e.g. Jane or water).
2. COMMON All ‘proper nouns’ (names of people, things, etc.) are –COMMON.
Thus Jane (referring to a specific person) is –COMMON, as is London. Other
nouns are +COMMON, e.g. dog, mankind or sincerity.
3. COUNT Nouns which can be made plural are +COUNT, e.g. dog. Nouns which are
–COUNT include water (in its usual sense), mankind or sincerity.
4. ANIMATE Nouns with the feature +ANIMATE are alive, those with –ANIMATE
are not.
5. HUMAN +HUMAN implies human, –HUMAN implies not human.
6. MALE +MALE implies male, –MALE implies not male (i.e. either female or
neither).
7. FEMALE +FEMALE implies female, -FEMALE implies not female (i.e. either male
or neither).

Semantic Features
Nouns can then be classified using sets of
these primitive features. For example:
Jane [–ABSTRACT,–COMMON,–COUNT,+ANIMATE,+HUMAN,–MALE,
+FEMALE]
boy [–ABSTRACT,+COMMON,+COUNT,+ANIMATE,+HUMAN,+MALE,-
FEMALE]
idea [+ABSTRACT,+COMMON,+COUNT,–ANIMATE,-HUMAN,-MALE,-
FEMALE]
sincerity [+ABSTRACT,+COMMON,–COUNT,–ANIMATE,-HUMAN,-MALE,-
FEMALE]

Reference
Richard Thomson
http://www.eecs.umich.edu/~rthomaso/documents/gener

Acknowledgement
Dr. Adel Elsayed
Research Leader, M3C Lab, University of Bolton, UK
Weiqiang Wei
Former PhD Student, University of Bolton, UK
Images have been stolen from Mrs. Web’s son
Master Google.

Syntax and semantics

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