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NaturalLanguageProcessing

whatit

does

whatisinvolved

whyisitdifficult

briefhistor

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sentencef structuredrepnsofmeaning

" " . Lisp:

(query

(file

detail

'date

"C:/help3.doc"))

"thelargecatchasedtherat" 1 1 1 1

L (E1s2 rodent(s2))L chased(s1,s2 )

"theyoungboyateabadapple" ... ...

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whatisinvolved

ie:symbols

manipulated

by

symbol

processors

search&inference

knowledgerepresentationtechniques

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whyisitdifficult

prejudice,politics,

etc

ambiguity...

s ntactic

semantic

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examplesentences

theold

man

the

boats

mycardrinkspetrol

IsawtheEiffelTowerflyingtoParis

heo ened

the

door

with

the

ke

heopenedthedoorwiththesqueakinghinge

theboykickedtheballunderthetree

theboy

kicked

the

wall

under

the

tree

putthebottlesintheboxontheshelfbythedoor

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(brief)historyoflanguageprocessing

1950s Russian

f Englishtranslation

1956 Chomsky

1960s Patternmatching

1970s Parsin

&some

KnRe

1980s Kn&inference

2000+ quietlypromising

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matchin :Student

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matchin :Elisa

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amodern inputsentenceapproach

morphological

processing

syntax

analysis

lexicon

semanticanal sis

grammar

semantic

rules

pragmaticcontextualana ys s

tar et

information

representation

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morphologicalprocessing

notes

all(?)spoken

lngs

exhibit

morphology

easiertohandleinwrittenlngsifnoticonic

somemorphologydescribesinfmbeyondsyntax

e : roximit Tamil

Setswana

etc

case

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mor holo exam les

Noun + Suffix S ntactic case Meanin

Chennai-ukku dative: destination To Madras

Chennai-ukku-irundu dative: source From MadrasChennai-le containment In Madras

Chennai-ai object (formal) Madras

Fig. 2.2. Suffix Attachment for Noun Cases (Tamil author's spelling)

Proximity Time Things (inanimate)ear -ppa t s t me: now -n t a t s t ng: t s

Far a-ppa (that time: then) a-ndtha (that thing: that)

Question e-ppa (what time: when) e-ndtha (what thing: which)

Fig. 2.3. Proximity Information as Prefix Tags (Tamil)

Proximity Cow Student

Near Speaker kgomo e (this cow) mo-ithuti yo (this student)

Near Listener k omo e-o that cow mo-ithuti o-o that student

Far kgomo e-le (that cow) mo-ithuti yo-le (that student)

Fig. 2.4. Proximity by Demostrative Pronoun Inflection (Setswana)

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step2

syntaxanalysis

objectives: 1 checkfor

correctness

2 producephrasestructure

uses

parser arulebasedsearchengine

lexicon dictionaryofwords&theircategories

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syntaxrules

partsof

speech

cons er

thecatchasesthemouse

alllarge

black

dogs

chase

cats

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example1

using

Lkit

(build-lexicon

'((a determiner) (cat noun) (dog noun)

(build-grammar'((s1 (sentence -> noun-phrase verb-phrase))

(np (noun-phrase -> determiner noun))

(vp (verb-phrase -> verb noun-phrase))

))

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example1

output

(parse 'sentence '(the dog chased a cat))

complete-edge 0 5 s1 sentence (the dog ...) nil

- - -

Syntax

(sentence(noun-phrase (determiner the) (noun dog))

(verb-phrase

(verb chased)

(noun-phrase (determiner a) (noun cat))))

Semantics

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sowhat?

wewantmean ng

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Remember:"theyoungboyateabadapple"

howcan

semantics

be

encoded

as

symbols?

young/old,happy/sad,good/bad?

owcansemant cs egenerate

whatcanbeinferredfromsemantics?

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Reminder:

"theyoungboyateabadapple"

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symbolicrepresentation

of

semantics

(actor (root boy) (id boy#732)

(tags animate human male)

(quant specific))

(action (primitve INGEST))(object (root apple) (id nil)

(tags physob veg fruit food)

(qual (phy-state -4))

(quant non-specific))

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semanticsin

lexicon

asimpleexample(build-lexicon

'((a det any )

(chased verb hunts )

(dog noun canine )

(the det specific)))

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semanticsin

grammar

rules

(s1 (sentence -> noun-phrase verb-phrase)

(actor . noun-phrase)

action . verb- hrase.action

(object . verb-phrase.object)

)

- -

(det . noun)

)

(vp (verb-phrase -> verb noun-phrase)(action . verb)

(object . noun-phrase)

)

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semantics

results

(parse 'sentence '(the dog chased a cat))

complete-edge 0 5 s1 sentence (the dog...) nil

s1 sentence -> (noun- hrase verb- hrase)

Syntax

(sentence (noun-phrase (det the) (noun dog))

-

(noun-phrase (det a) (noun cat))))

Semantics

(sentence (actor (specific canine))(action hunts)

(object (any feline)))

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semanticsin

lexicon

checks

1

(a det (sems . any))

(all det (sems . every))

. .

(cats noun (sems . feline) (num . plur))

(chase verb (sems . hunts) (num . plur))(chases verb (sems . hunts) (num . sing))

(dog noun (sems . canine) (num . sing))

(dogs noun (sems . canine) (num . plur))

(the det (sems . specific))

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semanticsin

grammar

checks

1


(actor . noun-phrase.sems)

action . verb- hrase.action


; check number of noun-phrase & verb-phrase

- .

= verb-phrase.number)

numeric-agreement-ok

numeric-agreement-bad)

)

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semantics

results

(parse 'sentence '(the dog chases a cat))



Syntax


-


Semantics

(sentence (actor specific canine)(action . hunts)

(object any feline)

numeric-agreement-ok)

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semantics

results

(parse 'sentence '(the dogs chases a cat))



Syntax


-


Semantics

(sentence (actor specific canine)(action . hunts)

(object any feline)

numeric-agreement-bad)

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semanticsin

grammar

checks

2


(fail if noun-phrase.number

/= verb- hrase.number


(action . verb-phrase.action)

. - .

)

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semantics

results

(parse 'sentence '(the dog chases a cat))

Semantics

sentence actor s ecific canine

(action . hunts)

(object any feline))


.... failed ....

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semanticsin

grammar

checks

3


(glitch numeric-agreement

if not noun- hrase.number

= verb-phrase.number)


. - .


)

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semantics

results


complete-edge 0 5 s1 sentence (the dogs...) nil

Glitches: numeric-a reement

s1 sentence -> (noun-phrase verb-phrase)

Syntax

-

(verb-phrase (verb chases)


Semantics(sentence (actor specific canine)

(action . hunts)

(object any feline))

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example2

lexicon

(a det any )

(cat noun feline )

(chase verb hunts )

(dog noun canine )

(the det specific)(black adj (color black))

(large adj (size 7/10))

(small adj (size 3/10))

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example2

grammar

(build-grammar

' n noun- hrase -> ?det *ad noun

(if det

(quantification . det)

(qualifiers . *.adj)

(object . noun)

))))

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example2

results

(parse 'noun-phrase '(small black dog))

complete-edge 0 3 np noun-phrase (small...) nil

n noun- hrase -> (?det *ad noun)

Syntax

(noun-phrase (adj small) (adj black) (noun dog))

(noun-phrase

(quantification undefined)

(qualifiers ((size . 3/10)) ((color . black)))(object canine))

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example2

results

small dogs chase the small cats

and large dogs chase the large cats

(sentence conjunction

.

(object . canine))

(action . hunts)

o ect quant . spec c qua s ze .

(object . feline)))

((actor (quant undefined) (qual (size . 7/10))

(object . canine))(action . hunts)

(object . feline))))

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semanticprocessing

(one

approach)

semantic

rules

in

grammarf

1st

stage

case

frame

verbformf primitiveactioncaseframe

disambiguate&

fill

additional

case

frame

slots

checkreferenceswithworldand/ordialog

dostatementlevelinference

integratewith

dialog

doeventse uencedialo

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step1:

produce

raw

case

frame

verb

casesthecatchasedtheratinthekitchen

thecatchasedtheratintothekitchen

commoncases

source starttime instrument

destination endtime beneficiary

location duration

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theambiguity

problem

eg:

the

boy

kicked

the

ball

under

the

tree

grammarrules

Sf SPP

f

NP f ?det *adj noun

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exampleframe

#1

actor (quant specific)

(tags animate male human)

(root boy)

action (root kick)

object (root ball)

(tags manip)

(posn-relative

(locator beneath)(object (root tree)

... ...

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exampleframe

#2

actor (quant specific)

(tags animate male human)

(root boy)

action (root kick)

object (root ball)

(tags manip)

dest (posn-relative

(locator beneath)(object (root tree)

... ...

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exampleverb

form

#1

primitive strike

slots instrument (part-of $actor foot)

legal start-time, end-time, duration

instrument, beneficiary, location

illegal source, dest

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exampleverb

form

#2

primitive push

slots instrument (part-of $actor foot)

legal source, dest, start-time, end-time,

instr, beneficiary, locatn, duration

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integrationwith

dialog

dialogshave...

players(actors)

props(objects)

locations

fromcase

frames

themes(derived)

plans(from

themes

and/or

derived)

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eventsequence

setof...

players(actors)

props(objects)

seriesof...

escapes,exceptions

&

alternatives

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readin rammars etc

A good source of links & references...

Computational Analysis of Prepositions http://knol.google.com/k/abdul-baqi-sharaf/computational-analysis-of-prepositions/3hc3uny2z7r41/4#

if you only plan to read one article...

Baldwin, T. Kordoni, V and Villavicencio, A. 2009. Prepositions in Applications: ASurvey and Introduction to the Special Issue ". Computational Linguistics 35 (2):119149.

also...

Litkowski, Kenneth C. and Orin Hargraves. 2007. SemEval-2007 task 06: Word-sense disambiguation of prepositions. In Proceedings of the 4th InternationalWorkshop on Semantic Evaluations, pages 2429, Prague.

Disambiguation of Preposition Sense Using Linguistically MotivatedFeatures, Stephen Tratz and Dirk Hovy. Proceedings of the NAACL HLT StudentResearch Workshop and Doctoral Consortium, pages 96100,

ou er, o ora o, une . c ssoc a on or ompu a ona ngu s cs

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,the NLP dictionary: www.cse.unsw.edu.au/~billw/nlpdict.html

for practical help with building grammars check the following (it is about 10 years

old but then so is the English language :o)A Grammar Writers Cookbook. Miriam Butt, Tracy Holloway King, Marma-EugeniaNio and Fridirique Segond

also (for writing larger grammars) it is useful to find a book on grammar for tutorsand/or students of English as a second language.

for a broad (if a little formal) take on semantics try dipping into...

Semantics-Oriented Natural Language Processing Mathematical Models andAlgorithms. Vladimir Fomichov A. 2010

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logic and knowledge representation a guide

htt : ds ace.dsto.defence. ov.au ds ace bitstream 1947 9996 1 DSTO-TR-2324%20PR.pdf

representing events for NLP

htt : www. oo le.co.uk url?sa=t&rct= & =knowled e%20re resentation%20%22representing%20events%22&source=web&cd=6&sqi=2&ved=0CEgQFjAF&url=http%3A%2F%2Fwww.aaai.org%2Focs%2Findex.php%2FFSS%2FFSS10%2Fpaper%2Fdownload%2F2183%2F2819&ei=f6oWT_e7DeKC4gTMpaijBA&usg=AFQjC

NFYmurwJR9oqfCRBimVprWRK45kew&cad=rja

semantic networks & frames (2005)

http://www.cs.bham.ac.uk/~jxb/IAI/w6.pdf

VERL: An Ontology Framework for Video Events (2005)

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1524892

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