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CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 1 Natural Language Understanding Outline: Motivation The SHRINK program, revisited Communicating.

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Presentation on theme: "CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 1 Natural Language Understanding Outline: Motivation The SHRINK program, revisited Communicating."— Presentation transcript:

1 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 1 Natural Language Understanding Outline: Motivation The SHRINK program, revisited Communicating with language Syntax Semantics Semantic grammars Augmented Transition Nets The STONEWORLD program

2 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 2 Motivation Make it easier for people to give commands to computers. Allow computers to perform language translation. Allow computers to listen to lectures and read books, in order alleviate the knowledge acquisition bottleneck. Integrate robots into human society.

3 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 3 Levels of Analysis for NLU (Read up from the acoustic level to the pragmatic level) Pragmatic level (goals, intents, dialog, rhetorical structure, speech acts) Semantic level (meaning, representation) Syntactic level (grammar, phrase structure) Lexical, Morphological level (words, inflections) Phonological level (acoustic features -- phonemes) Acoustic level (sensing, signal processing)

4 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 4 The SHRINK Program, revisited Holds a conversation with the user. Works primarily at the pragmatic level, glossing over the semantic level, and ignoring or simplifying analysis at the other levels. Illustrates how shallow a program’s knowledge can be and still present an image of understanding. Demonstrates key ideas from J. Weizenbaum’s ELIZA program, published in 1966.

5 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 5 Mechanisms in SHRINK Processing is oriented towards maintaining an illusion of understanding. Pattern matching used to “parse” user input. The YOU-ME-MAP function transposes first and second person references. Keyword-based rules respond to certain topics such as dreams, love, being positive or negative. Questions to the SHRINK are transformed into questions to the user. When all other rules fail, PUNT responses are used.

6 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 6 A Sample Dialog with SHRINK (shrink) WELCOME TO MY SOFA! PLEASE ENCLOSE YOUR INPUT IN PARENTHESES. (hi there) TELL ME MORE (i have a little problem) HOW LONG HAVE YOU HAD A LITTLE PROBLEM? (ever since i told my girlfriend that i love computers more than her) ALL IS FAIR IN LOVE AND WAR (thanks maybe i should have told her that) BE MORE DECISIVE (ok) I SEE (bye) GOODBYE

7 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 7 Syntax, Semantics, Pragmatics By taking a more systematic approach to NLU at these levels, we will be able to create more useful and reliable natural language interfaces. Issues to resolve: What is the ultimate purpose of language, and how does that influence NLU? How do phrase-structure grammars work? How can meaning be interpreted and represented? How can the syntax and semantics of a system be designed to match the needs of an application?

8 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 8 Communicating with Language Language is for communication. Communication usually means sending and receiving information. Sentences describe events, states of the world, objects and ideas, feelings and attitudes, and hypothetical situations. Phrase-structure grammars provide a method of structuring messages, allowing for a great variety of possible meanings.

9 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 9 Syntax Describes the form, not meaning, of sentences in a language. Syntax is traditionally described with formal systems called grammars. A context free grammar can be specified with 4 components: G = (Σ, V, S, P), where Σ is a finite set of terminal symbols called the alphabet. V is a finite set of nonterminal symbols. S is a distinguished member of V called the start symbol. P is a finite set of productions.

10 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 10 Example Grammar G = ({0, 1}, {S, A, B}, S, P), where P = { S -> 01S S -> 10S S -> 0S1 S -> 1S0 S -> 01 S -> 10 }

11 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 11 Example Grammar 2 G = ({symbols, are, tools}, {S, N, V}, S, P), where P = { S -> NVN N -> symbols N -> tools V -> are } A derivation of a sentence from S: S -> NVN -> tools VN -> tools are N -> tools are symbols Each item in the sequence is a sentential form.

12 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 12 Exercise For each of the strings below, determine whether or not it is in L(G), the language generated by G. If it’s in the language, give a derivation. 01 λ 011001 01S10 101S101 G = ({0, 1}, {S, A, B}, S, P), where P = {S -> 01S, S -> 10S, S -> 0S1, S -> 1S0, S -> 01, S -> 10}

13 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 13 Semantics Representation of meaning using case frames. The verb structures the frame: “Alexander took an exam.” Agent: Alexander Action: take (write, submit to) Object: exam Time: past

14 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 14 Semantic Grammar A semantic grammar is a grammar whose syntactic categories correspond directly to groups of words whose meanings can be largely inferred from the parse. -> the -> do | perform | start | finish -> job | task | command | activity | operation “start the activity” “do the operation” “finish the job”

15 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 15 Augmented Transition Nets An ATN is a language processor that combines parsing and translation. It is based on a collection of transition diagrams. the do, etc. job, etc

16 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 16 Stone World A microworld: 2-D cellular space in which various objects can be placed. An agent “Mace” that takes commands from the user, and which inhabits the microworld. Stationary objects: pillars, wells, quarries. Portable objects: stones, gems. Actions: Mace can move and can carry objects. A natural-language interface: Augmented transition network based on a semantic grammar.

17 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 17 Stone World Motivation Demonstrates a full combination of syntax, semantics, actions, and responses. An artificial, closed world permits unambiguous interpretation. Stone World offers a substrate upon which experiments can games can be constructed. Stone World, while simple by comparison, shares these features with the well-known research system SHRDLU, developed by Terry Winograd at MIT.

18 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 18 Stone World’s ATN SHOW * LASTG1T2T3T4 P2P3 G2G3 DOWN, * IT DOWN, (PUT-VERB) (TAKE-VERB) UP, (GO-VERB) * TO (DNP1) TOWARD (DNP1) * G1(NP1)

19 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 19 Stone World’s ATN (Cont) (ARTICLE)(OBJ-NOUN) (ARTICLE) (OBJ-NOUN) (DIRECTION-NOUN) DNP1DNP2 NP1NP2

20 CSE 415 -- (c) S. Tanimoto, 2004 Natural Language Understanding 20 Sample Conversation WALK NORTH * I UNDERSTAND YOU. OK GO TO THE WEST * I UNDERSTAND YOU. OK GO WEST * I UNDERSTAND YOU. OK TAKE A STONE FROM THE QUARRY * I UNDERSTAND YOU. OK DROP THE STONE TOWARD THE EAST * I UNDERSTAND YOU. OK TAKE A STONE * I UNDERSTAND YOU. OK DROP IT TO THE NORTH * I UNDERSTAND YOU. OK GO SOUTH * I UNDERSTAND YOU. OK


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