This presentation contains description of levels of knowledge,grammar & languages,basic parsing techniques,recursive transition network & augmented transition network RTN & ATN

1. Natural Language Processing
BY SAURABH KAUSHIK (3174)
SARVESH RAWAT (3121)
SHAFAQ ALI (3122)

2. Overview of Linguistic
 Each human language is a complex of knowledge and abilities enabling
speakers of the language to communicate with each other, to express
ideas, hypotheses, emotions, desires, and all the other things that need
expressing.
 Linguistics is the study of these knowledge systems in all their aspects:
how is such a knowledge system structured, how is it acquired, how is it
used in the production and comprehension of messages, how does it
change over time? Linguists consequently are concerned with a number of
particular questions about the nature of language.

3. Levels of Language
Phonetic and phonological knowledge
Morphological knowledge
Syntactic knowledge
Semantic knowledge
Pragmatic knowledge
World knowledge

4. Phonetic and phonological knowledge
 This is knowledge which relates sounds to
the words we recognize.
 A phoneme is the smallest unit of sounds.
 Phones are aggregated into word sounds

5. Morphological knowledge
 This is lexical knowledge which relates to word
constructions from basic units called morphemes.
 A morpheme is the smallest unit of meaning.
 E.g. the construction of friendly from the root ‘friend’
and the suffix ‘ly’.

6. Syntactic knowledge
 This knowledge relates to how words are put together
or structured to form grammatically correct sentences
in the language

7. Semantic knowledge
 This knowledge is concerned with the meanings of
words and phrases and how they combine to form
sentence meanings.

8. Pragmatic knowledge
 This is high-level knowledge which relates to the use
of sentences in different contexts and how the
context affects the meaning of the sentences.

9. World knowledge
 World knowledge relates to the language a user must
have in order to understand and carry on a
conversation.
 It must include an understanding of the other
person’s beliefs and goals.

10. Grammars & Languages
 Alphabet (vocabulary): Σ
 Concatenation operations
 Σ* : set of all strings that can be formed with symbols of Σ
 Language: L ⊆ Σ*
 Given a string w1
n of Σ*:
w1
n = w1, …, wn
wi ∈ Σ
 We have to determine if w1
n ∈ L

11. Grammars & Languages
<V, Σ, P, S>
Non-terminal vocabulary
(set of variables)
Terminal vocabulary
(alphabet)
Production set
Initial variable

12. Example
Production Rules: S NP VP
NP ART N
VP V NP
N boy|popsicle|frog
V ate|kissed|flew
ART the|a
(S = starting symbol, NP = noun phrase, VP = verb phrase, N = noun, V = verb & ART = Article)
Sentence Generated : The boy ate a popsicle,The frog kissed a boy,A boy ate the frog.

13. Grammar Languages Automaton
Type-0 Recursively enumerable Turing machine
Type-1 Context-sensitive
Linear-bounded non-
deterministic Turing machine
Type-2 Context-free
Non-deterministic pushdown
automaton
Type-3 Regular Finite state automaton

14. Chomsky Hierarchy of Grammar
 Type 0 G :- xyz xwz , where y cannot be empty string.
 Type 1 G :- S aS; AB BA; |L.H.S|<=|R.H.S.|
 Type 2 G :- S aSb; A BC; here |L.H.S.|=1
 Type 3 G :- A aB;A a; Most restrictive grammer

15. Structural Representation

16. Basic Parsing Techniques
 Parsing technique, the method of analyzing a sentence to
determine its structure according to the grammar
 The most common way of representing how a sentence is
broken into its major subparts (constituents), and how those
subparts are broken up in turn, is a tree.

17. Basic Parsing Techniques
Lexicon Table

18. Transition Network
 Transition Network used to represent formal and natural language
structures.
 They are formed using directed graphs and finite state automata.
 It consist of No. of nodes and labeled arcs.
 The nodes represent different states in traversing a sentence & the arcs
represent rules or test conditions required to make the transition from one
state to the next.
 A path through a T.N. corresponds to a permissible sequence of word
types for a given grammar

19. Example
Sentences:-
a. Big white fluffy clouds.
b. Our bright children.
c. A large beautiful white
flower.
d. Large green leaves.
e. Buildings.
f. Boston’s best seafood
restaurants.

20. Top-Down V/S Bottom-up Parsing
Top-Down Parsing Bottom-Up Parsing

21. Deterministic V/S Non-Deterministic
Network

22. Recursive T.N.
Recursive T.N. is a T.N. which permits arc labels to refer to other networks

23. Augmented T.N.
 When we include semantic information with grammar then
performance of parser increases.
 We can achieve the additional capabilities by augmenting a
RTN with the ability to perform additional tests and store
immediate results as a sentence is being parsed, then
resulting T.N. is called an Augmented Transition Network.

24. THANK-YOU!