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1 CSE573 Autumn 1997 02/23/98 Natural Language Processing Administrative PS3 due today PS4 out Wednesday, due Friday 3/13 (last day of class) special end-of-quarter offer: turn in at the final costs 2 late days! Last time the Graphplan algorithm This time Graphplan Natural language processing

CSE573 Autumn 1997 1 02/23/98 Natural Language Processing Administrative –PS3 due today –PS4 out Wednesday, due Friday 3/13 (last day of class) special

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Page 1: CSE573 Autumn 1997 1 02/23/98 Natural Language Processing Administrative –PS3 due today –PS4 out Wednesday, due Friday 3/13 (last day of class) special

1 CSE573 Autumn 1997

02/23/98 Natural Language Processing

• Administrative– PS3 due today

– PS4 out Wednesday, due Friday 3/13 (last day of class)

• special end-of-quarter offer: turn in at the final costs 2 late days!

• Last time– the Graphplan algorithm

• This time– Graphplan

– Natural language processing

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2 CSE573 Autumn 1997

NLP Perspective

• An interesting cognitive problem – language is the most “human” communication modality, so it seems

impossible to understand human intelligence without understanding how language works

– Turing test looked on ability to communicate in an unrestricted natural language dialogue as the definition of intelligence

• An interesting practical problem: incredible extensions to usefulness of computers if problems could be solved in – speech recognition and understanding (no more phone menus!)

– handwriting recognition and understanding (a PDA that actually works)

– machine translation (electronic funds transfers and more complex multi-national transactions)

– text recognition (intelligent information retrieval)

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The main problem

• The problem is not so well defined: take {spoken/written/textual} language as input, and ...

• Understanding language is “AI Complete”– in order to do it you have to understand every other facet of intelligence as

well --- planning, reasoning about physical systems, geometrical and spatial reasoning, diagnosis, etc. etc.

• The history of natural language processing in AI is a process of discovering just how difficult and deep the problem is

• Ways to make the problem easier– work in limited domains (newspaper stories about earthquakes)

– work with simpler syntax (will respond to information requests or to simple commands but cannot understand arbitrary sentences about the domain). Example: electronic funds transfers; intelligent database front-ends; Truckworld scenarios

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The usual breakdown of language processing tasks

• Signal understanding: translate signals (spoken speech or written characters) into some internal symbolic form. Produce phonemes or characters.

• Phonology: group phonemes into morphemes

• Morphology: group morphemes into words

• Syntax: parse words into phrases, phrases into sentences

• Semantics: connect words to objects and concepts in some internal representation language

• Pragmatics: infer what is desired from what is said in a sentence

• Discourse: constructing an argument, negotiating an agreement, (communication among agents)

We are here

Bottom up processing

Top down processing

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Our Main Task: A Command Processor

• The system will parse, interpret and execute commands in a simple world– Blocks world (in class):

• “Pick up the green sphere on top of the yellow cube”

• “Put it down next to the red cube.”

– Truckworld (for the problem set): • “Recycle the red broken glass.”

• “Refuel using the fuel drum at position 7.”

• Parsing: is the sentence well formed?

• Semantic Interpretation: – does the command make sense given the current state of the world?

– what do the pronouns refer to?

• Execution: simple call to an execution system (Macrops)

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Our Limited Problem

1 2 3 4 5

• Arm can lift at most one object at a time• Pyramid can be put on top of another block but not below• Sphere cannot be put on top or below any block

Actions• pick up top block at current position• put down block being held • move the gripper to another position

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Goal of the exercise

• Parse commands, flagging those that are grammatically incorrect

• Verify that the command is legal– does a pickup sentence refer to a single object

– is the gripper at the same location as that object

– is the object at the top of the stack

– is the gripper empty

• If so, “execute it”

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Sample Sentences: Grammatical and Feasible

• Pick up the blue pyramid.• Pick up a green block.• Pick up a cube.• Lift the block at position 5.• Move to position 3.• Move to a cube.• Put it down.• Drop the red cube.• Put down a block.

(Feasible under the propercircumstances)

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Sample Sentences: Ungrammatical

• Break the pyramid.• Lift a blocks.• Pick up block.• Pick up the green blue pyramid cube.• Move.

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Sample Sentences: Grammatical but Infeasible

• Pick up the cubes.

• Move to position 8.

• Pick up the cube; Move to 3; Pick up the green sphere

• Pick up the green sphere; Move to 2; Put it down.

• Pick up a cube; Move to the pyramid; Put down the cube.

• Pick up the cube.

• Pick up a red sphere.

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Morphology (the Lexicon)

• The Lexicon (dictionary) is a list of all recognizable words

• Naive approach, just list them

• Redundancy problem– inconsequentially is probably best stored as a variant of the root word

consequent, along with a note that it was negated, and the fact that it is an adverb

• Additional information required– part of speech (rock is both a noun and a verb)– singular or plural (nouns)– tense (verb)– can the verb take an object? (hit versus cried)

• Some typical lexicon entries– (glasses (n (agr p) (root glass))– (detonate (v (tense present) (object t)))– (explode (v (tense present) (object t) (root detonate)))

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Lexicon for the Example

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Parsing

• The task: – take as input a sentence (list of symbols/words) and a grammar

– produce as output• whether or not the sentence is grammatical?

• a parse tree?

• Grammar as rewrite rules:

S NP VP NP

NP ADJS NounNP Det ADJS Noun

ADJS ADJS Adj ADJS

VP VerbVP Adverb Verb

Det aDet anDet the

Noun rockNoun glassNoun glassesNoun Fred

AdjheavyAdjbrokenAdjred

Actually these are lexicon entrieslike on the previous slide

VerbbreaksVerbrecyclesVerb“Picks up”

AdvquicklyAdvcarefully

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Top-down and bottom-up rewrites

S NP VP NP

NP ADJS NounNP Det ADJS Noun

ADJS ADJS Adj ADJS

VP VerbVP Adv Verb

S NP VP NP ADJS Noun VP NP Noun VP NPFred VP NPFred Adverb Verb NPFred carefully Verb NPFred carefully recycles NPFred carefully recycles Det ADJS Noun Fred carefully recycles the ADJS NounFred carefully recycles the Adj ADJS NounFred carefully recycles the heavy ADJS NounFred carefully recycles the heavy Adj ADJS NounFred carefully recycles the heavy red ADJS NounFred carefully recycles the heavy red NounFred carefully recycles the heavy red rock

Fred carefully recycles the heavy red rockNoun Adv Verb Det Adj Adj NounADJS Noun Adv Verb Det Adj Adj NounNP Adv Verb Det Adj Adj NounNP VP Det Adj Adj ADJS NounNP VP Det Adj ADJS NounNP VP Det ADJS NounNP VP NPS

To parse: Fred carefully recycles the heavy red rock

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The Parse Tree

Fred carefully recycles the heavy red rock.

S

NP VP NP

NounADJS Adverb Verb Det ADJS Noun

ADJSAdj

ADJSAdj

Fred carefully recyclesthe

heavy

red

rock

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Grammar for the Example (first cut)