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Informa(onExtrac(on
WeiXu(many slides from Greg Durrett, Luheng He, Emma Strubell)
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ThisLecture
‣ Howdowerepresentinforma(onforinforma(onextrac(on?
‣ OpenInforma(onExtrac(on
‣ Rela(onextrac(on
‣ Slotfilling
‣ Seman(crolelabeling/abstractmeaningrepresenta(on
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IE:TheBigPicture
‣ Howdowerepresentinforma(on?Whatdoweextract?
‣ Slotfillers‣ En(ty-rela(on-en(tytriples(fixedontologyoropen)
‣ Seman(croles
‣ Abstractmeaningrepresenta(on
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Seman(cRoleLabeling
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Seman(cRoleLabeling
‣ Findout5Wintext—“whodidwhattowhom,whenandwhere”
‣ Iden(fypredicate,disambiguateit,iden(fythatpredicate’sarguments
FigurefromHeetal.(2017)
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Ques(on-AnswerDrivenSRL
FigurefromFitzGeraldetal.(2018)
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Seman(cRoleLabeling
My mug broke into pieces immediately.
The robot broke my favorite mug with a wrench.
Semantic Role Labeling (SRL)
3 FigurefromHeetal.(2017)
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Seman(cRoleLabeling
FigurefromHeetal.(2017)
My mug broke into pieces immediately.
The robot broke my favorite mug with a wrench.
Semantic Role Labeling (SRL)
3
vsubj obj prep
subj v prep adv
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Seman(cRoleLabeling
My mug broke into pieces immediately.
The robot broke my favorite mug with a wrench.
Semantic Role Labeling (SRL)
3
vsubj obj prep
subj v prep adv
thing broken
thing broken
breaker instrument
pieces (final state) temporal
FigurefromHeetal.(2017)
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Seman(cRoleLabeling
My mug broke into pieces immediately.
The robot broke my favorite mug with a wrench.
Semantic Role Labeling (SRL)
3
vsubj obj prep
Frame: break.01role description
ARG0 breakerARG1 thing brokenARG2 instrumentARG3 pieces
ARG4 broken away from what?
subj v prep adv
thing broken
thing broken
breaker instrument
pieces (final state) temporal
ARG0 ARG1 ARG2
ARG3ARG1 ARGM-TMP
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�11 4
The Proposition Bank (PropBank)
Core roles: Verb-specific roles (ARG0-
ARG5) defined in frame files
Frame: break.01
role descriptionARG0 breakerARG1 thing broken
ARG2 instrument
ARG3 pieces
ARG4 broken away from what?
Frame: buy.01
role descriptionARG0 buyerARG1 thing bough
ARG2 seller
ARG3 price paid
ARG4 benefactive
role descriptionTMP temporalLOC locationMNR mannerDIR directionCAU causePRP purpose…
Adjunct roles: (ARGM-) shared
across verbs
Annotated on top of the Penn Treebank Syntax
PropBank Annotation Guidelines, Bonial et al., 2010
4
Paul Kingsbury and Martha Palmer.From Treebank to PropBank. 2002TheProposi(onBank(PropBank)
FigurefromHeetal.(2017)
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Seman(cRoleLabeling
FigurefromHeetal.(2017)
‣ Iden(fypredicates(love)usingaclassifier(notshown)
‣ Iden(fyARG0,ARG1,etc.asataggingtaskwithaBiLSTMcondi(onedonlove
‣ Othersystemsincorporatesyntax,jointpredicate-argumentfinding
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Residual/HighwayConnec(ons
�1323
input from the previous layer
recurrent input
from the prev. timestep
output to the next layer
References: Deep Residual Networks, Kaiming He, ICML 2016 Tutorial
Training Very Deep Networks, Srivastava et al., 2015
Non-linearity
ht shortcut
ht�1 F(ct�1,ht�1,xt)
residual netht + xt
gated highway network:
rt � ht + (1� rt) � xt
rt = �(f(ht�1,xt))
xt
xt
new output:
Model - (2) Highway ConnectionsDeep BiLSTM Tagger Highway Connections Variational
DropoutViterbi Decoding w\
Hard Constraints
23
input from the previous layer
recurrent input
from the prev. timestep
output to the next layer
References: Deep Residual Networks, Kaiming He, ICML 2016 Tutorial
Training Very Deep Networks, Srivastava et al., 2015
Non-linearity
ht shortcut
ht�1 F(ct�1,ht�1,xt)
residual netht + xt
gated highway network:
rt � ht + (1� rt) � xt
rt = �(f(ht�1,xt))
xt
xt
new output:
Model - (2) Highway ConnectionsDeep BiLSTM Tagger Highway Connections Variational
DropoutViterbi Decoding w\
Hard Constraints
FigurefromHeetal.(2017)
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SRLSystems
�1416
SRL Systems
syntactic features
candidate argument spans
labeled arguments
prediction
labeling
ILP/DP
sentence, predicate
argument id.
Pipeline Systems
Deep BiLSTM
Hard constraints
BIO sequence
prediction
sentence, predicate
*This work
Punyakanok et al., 2008 Täckström et al., 2015 FitzGerald et al., 2015
sentence, predicate
BIO sequence
prediction
Deep BiLSTM + CRF layer
Viterbi
context window features
End-to-end Systems
Collobert et al., 2011 Zhou and Xu, 2015 Wang et. al, 2015
He et al., 2017
The System on previous slide
FigurefromHeetal.(2017)
(syntax-based)
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[LISA]
10YearsofPropBankSRL
F1 Syntax-based
End-to-enddeep NN
[FitzGerald, Täckström, Ganchev, Das]
[Täckström, Ganchev, Das]
[Zhou & Xu]
[He, Lee, Lewis, Zettlemoyer] [He, Lee, Levy,
Zettlemoyer]
[Tan, Wang, Xie, Chen, Shi]
[Toutanova, Haghigi, Manning][Punyakanok, Roth, Yih]
FigurefromStrubelletal.(2018)
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Seman(cRoleLabeling
‣ Canwecombinethetwoapproaches—incorporatesyntac(cinforma(onintoneuralnetworks?
‣Mul(-tasklearningwithrelatedtasks,e.g.,part-of-speechtagging,dependencyparsing…
‣ Syntac(cally-informedself-afen(on:usetheTransformertoencorethesentence;inonehead,tokenafendstoitslikelysyntac(cparents;innextlayer,tokensobserveallotherparents.
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committee awards Strickland advanced opticswhoNobelp+1
Recall:Transformer(mul(-headself-afen(on)
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Multi-head self-attention + feed forward
Multi-head self-attention + feed forward
Layer 1
Layer p
Multi-head self-attention + feed forwardLayer J
committee awards Strickland advanced opticswhoNobel
Recall:Transformer(mul(-headself-afen(on)FigurefromStrubelletal.(2018)
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Layer p
QKV
MH
M1
Feed Forward
Feed Forward
Feed Forward
Feed Forward
Feed Forward
Feed Forward
Feed Forward
biaffine parser
biaffine parser
biaffine parser
biaffine parser
biaffine parser
biaffine parser
biaffine parser
[Dozat and Manning 2017]committee awards Strickland advanced opticswhoNobel
optics advanced
who Strickland
awards committee
NobelA
Syntac(cally-InformedSelf-Afen(on
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committee awards Strickland advanced opticswhoNobel
Syntac(cally-InformedSelf-Afen(on
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Syntactically-informed self-attention
Multi-head self-attention + feed forwardLayer 1
Layer p
Multi-head self-attention + feed forwardLayer J
committee awards Strickland advanced opticswhoNobel
Linguis(cally-InformedSelf-Afen(onFigurefromStrubelletal.(2018)
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Layer p Syntactically-informed self-attention
Multi-head self-attention + feed forwardLayer J
Linguis(cally-InformedSelf-Afen(on
Layer 1 Multi-head self-attention + feed forward
Multi-head self-attention + feed forwardLayer r
NNP NN VBZ/PRED NNP WP VBN/PRED NN
committee awards Strickland advanced opticswhoNobel
FigurefromStrubelletal.(2018)
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Layer 1
Syntactically-informed self-attentionLayer p
Multi-head self-attention + feed forwardLayer J
Multi-head self-attention + feed forward
Layer r Multi-head self-attention + feed forward
nn nsubj root dobj nsubj rcmod dobj
committee awards Strickland advanced opticswhoNobel
NNP NN VBZ/PRED NNP WP NNVBN/PRED
Linguis(cally-InformedSelf-Afen(onFigurefromStrubelletal.(2018)
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Layer 1 Multi-head self-attention + feed forward
committee awards Strickland advanced opticswhoNobel
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
Linguis(cally-InformedSelf-Afen(onFigurefromStrubelletal.(2018)
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committee awards Strickland advanced opticswhoNobel
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
Linguis(cally-InformedSelf-Afen(onFigurefromStrubelletal.(2018)
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committee awards Strickland advanced opticswhoNobel
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
class labels
Linguis(cally-InformedSelf-Afen(onFigurefromStrubelletal.(2018)
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committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
Linguis(cally-InformedSelf-Afen(on
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committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
Linguis(cally-InformedSelf-Afen(on
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committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
I-ARG0 B-V B-ARG1 O O O
Linguis(cally-InformedSelf-Afen(on
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committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
I-ARG0 B-V B-ARG1 O O OLinguis(cally-InformedSelf-Afen(on
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committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
I-ARG0 B-V B-ARG1 O O OLinguis(cally-InformedSelf-Afen(on
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committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
Syntactically-informed self-attention
Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
I-ARG0 B-V B-ARG1 O O OLinguis(cally-InformedSelf-Afen(on
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Layer r Multi-head self-attention + feed forward
Layer p
Multi-head self-attention + feed forwardLayer J
nn nsubj root dobj nsubj rcmod dobj
NNP NN VBZ/PRED NNP WP NNVBN/PRED
Syntactically-informed self-attention
committee awards Strickland advanced opticswhoNobel
B-ARG0
argspredicates
Bilinear
I-ARG0 B-V B-ARG1 O O OO O O B-ARG0 B-R-ARG0 B-V B-ARG1
pospreds
labeledparse
SRL
Linguis(cally-InformedSelf-Afen(on
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GloVe ELMo
in-domain (dev) in-domain (dev)
He et al. 2017 81.5 ---
He et al. 2018 81.6 85.3
SA 82.39 85.26
LISA 82.24 85.35
+D&M 83.58 85.17
+Gold 86.81 87.63
Strubelletal.(2018)
Linguis(cally-InformedSelf-Afen(on
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WhySRLisdifficult?orNLPingeneral
‣ Syntac(cAlterna(onThe robot plays piano.
The music plays softly.
ARG0player
ARG1thing performed
ARG2instrument
ARGM-MNR
The cafe is playing my favorite song.
ARG1thing performed
ARG0player
subjects
objects
6
Syntactic Alternation PP Attachment Long-range Dependencies
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‣ Preposi(onalPhrase(PP)Afachment
I eat [pasta] [with delight].ARG0eater
ARG1meal
ARGM-MNRmanner
I eat [pasta with broccoli].ARG0eater
ARG1meal
7
Syntactic Alternation Prepositional Phrase (PP) Attachment Long-range
Dependencies
WhySRLisdifficult?orNLPingeneral
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8
We flew to Chicago.ARG1
passengerARGM-GOL
goal
We remember the nice view flying to Chicago.ARG1
passengerARGM-GOL
goal
We remember John and Mary flying to Chicago.ARG1
passengerARGM-GOL
goal
Syntactic Alternation PP Attachment Long-range Dependencies‣ LongDependencies
WhySRLisdifficult?orNLPingeneral
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‣ Evenharderforout-of-domaindataSRL is even harder for out-domain data …
“Dip chicken breasts into eggs to coat”
Active, Ser133-phosphorylated CREB effects transcription of CRE-dependent genes via interaction with the 265-kDa …
9
WhySRLisdifficult?orNLPingeneral
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AbstractMeaningRepresenta(on
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AbstractMeaningRepresenta(on
‣ Graph-structuredannota(on
‣ Nodesarevariableslabeledbyconcepts;edgesareseman(crela(onsAMR – Abstract Meaning Representation
“Bob ate four cakes that he bought.”(x2 / eat-01
:ARG0 (x1 / person
:name (n / name
:op1 "Bob")
:wiki "Bob_X")
:ARG1 (x4 / cake
:quant 4
:ARG1-of (x7 / buy-01
:ARG0 x1)))
e / eat-01
x4 / cakex1 / person
x7 / buy-01
"Bob_X"
name
4
FigurefromGruzi(setal.(2014)
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AbstractMeaningRepresenta(on
Banarescuetal.(2014)
‣ SupersetofSRL:fullsentenceanalyses,containscoreferenceandmul(-wordexpressionsaswell
‣ F1scoresinthe60s:hard!
‣ Socomprehensivethatit’shardtopredict,buts(lldoesn’thandletenseorsomeotherthings…
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Summariza(onwithAMR
Liuetal.(2015)
‣MergeAMRsacrossmul(plesentences
‣ Summariza(on=subgraphextrac(on
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SlotFilling
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SlotFilling‣Mostconserva(ve,narrowformofIE
IndianExpress—Amassiveearthquakeofmagnitude7.3struckIraqonSunday,103kms(64miles)southeastofthecityofAs-Sulaymaniyah,theUSGeologicalSurveysaid,reportsReuters.USGeologicalSurveyiniKallysaidthequakewasofamagnitude7.2,beforerevisingitto7.3.
magnitude time
epicenter
Speaker:AlanClark
“GenderRolesintheHolyRomanEmpire”
AllagherCenterMainAuditorium
Thistalkwilldiscuss…
speakertitle
location
FreitagandMcCallum(2000)
‣ Oldwork:HMMs,laterCRFstrainedperrole
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SlotFilling:MUC
HaghighiandKlein(2010)
‣ Keyaspect:needtocombineinforma(onacrossmul(plemen(onsofanen(tyusingcoreference
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SlotFilling:Forums
‣ Extractcode-relatedconceptsinsoowareengineeringforums,butnoteverythingthatlookslikeaconceptisaconcept(e.g.,windows)
avariablenameinthiscontext
JeniyaTabassum,MounicaMaddela,WeiXu,AlanRi8er.“CodeandNamedEn?tyRecogni?oninStackOverflow”inACL(2020)
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Rela(onExtrac(on
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Rela(onExtrac(on‣ Extracten(ty-rela(on-en(tytriplesfromafixedinventory
ACE(2003-2005)
DuringthewarinIraq,AmericanjournalistsweresomeKmescaughtinthelineoffire
Located_In
‣ Systemscanbefeature-basedorneural,lookatsurfacewords,syntac(cfeatures(dependencypaths),seman(croles
Na(onality
‣ Problem:limiteddataforscalingtobigontologies
‣ UseNER-likesystemtoiden(fyen(tyspans,classifyrela(onsbetweenen(typairswithaclassifier
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HearstPaferns
Hearst(1992)
Xsuchas[list] ciKessuchasBerlin,Paris,andLondon.
‣ Syntac(cpafernsespeciallyforfindinghypernym-hyponympairs(“isa”rela(ons)
Berlinisacity
otherciKesincludingBerlin
YisaX
otherXincludingY
‣ Totallyunsupervisedwayofharves(ngworldknowledgefortaskslikeparsingandcoreference(BansalandKlein,2011-2012)
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DistantSupervision
Mintzetal.(2009)
[StevenSpielberg]’sfilm[SavingPrivateRyan]islooselybasedonthebrothers’story
‣ Iftwoen((esinarela(onappearinthesamesentence,assumethesentenceexpressestherela(on
‣ Lotsofrela(onsinourknowledgebasealready(e.g.,23,000film-directorrela(ons);usethesetobootstrapmoretrainingdata
Allisonco-producedtheAcademyAward-winning[SavingPrivateRyan],directedby[StevenSpielberg]
Director
Director
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DistantSupervision
Mintzetal.(2009)
‣ Learndecentlyaccurateclassifiersfor~100Freebaserela(ons‣ Couldbeusedtocrawlthewebandexpandourknowledgebase
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DistantSupervision
FigurefromJiangetal.(2016)
‣ Inherentlyhavenoiseintrainingdata,needspecialmethods(e.g.,mul(-instancelearning)tohandlefalseposi(vesANDfalsenega(ves.
falseposi(ve
???
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Mul(-instanceLearning
Xuetal.(2013),Pershinaetal.(2014),Tabassum(2016)
Nega%ve'Bags' Posi%ve'Bags''
A'bag'is'labeled'posi%ve,'if''there'is'at#least#one'posi%ve'example'
A'bag'is'labeled'nega%ve,'if''all'the'examples'in'it'are'nega%ve'
‣ Insteadoflabelsoneachindividualinstance,thelearneronlyobserveslabelsonbagsofinstances.
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Mul(-instanceLearning
Xuetal.(2013),Pershinaetal.(2014),Tabassum(2016)
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OpenIE
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OpenInforma(onExtrac(on
‣ Typicallynofixedrela(oninventory
‣ “Open”ness—wanttobeabletoextractallkindsofinforma(onfromopen-domaintext
‣ Acquirecommonsenseknowledgejustfrom“reading”aboutit,butneedtoprocesslotsoftext(“machinereading”)
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TextRunner‣ Extractposi(veexamplesof(e,r,e)triplesviaparsingandheuris(cs
BarackObama,44thpresidentoftheUnitedStates,wasbornonAugust4,1961inHonolulu
=>Barack_Obama,wasbornin,Honolulu
‣ TrainaNaiveBayesclassifiertofiltertriplesfromrawtext:usesfeaturesonPOStags,lexicalfeatures,stopwords,etc.
‣ 80xfasterthanrunningaparser(whichwasslowin2007…)
Bankoetal.(2007)
‣ Usemul(pleinstancesofextrac(onstoassignprobabilitytoarela(on
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Exploi(ngRedundancy
Bankoetal.(2007)
‣ Concrete:definitelytrueAbstract:possiblytruebutunderspecified
‣ Hardtoevaluate:canassessprecision ofextractedfacts,buthowdoweknowrecall?
‣ 9Mwebpages/133Msentences
‣ 2.2tuplesextractedpersentence,filterbasedonprobabili(es
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ReVerb
Faderetal.(2011)
‣Moreconstraints:openrela(onshavetobeginwithverb,endwithpreposi(on,becon(guous(e.g.,wasbornon)
‣ Extractmoremeaningfulrela(ons,par(cularlywithlightverbs
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ReVerb
Faderetal.(2011)
‣ Foreachverb,iden(fythelongestsequenceofwordsfollowingtheverbthatsa(sfyaPOSregex(V.*P)andwhichsa(sfyheuris(clexicalconstraintsonspecificity
‣ Findthenearestargumentsoneithersideoftherela(on
‣ Annotatorslabeledrela(onsin500documentstoassessrecall
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Takeaways
‣ Rela(onextrac(on:cancollectdatawithdistantsupervision,usethistoexpandknowledgebases
‣ Slotfilling:(edtoaspecificontology,butgivesfine-grainedinforma(on
‣ OpenIE:extractslotsofthings,buthardtoknowhowgoodorusefultheyare
‣ Cancombinewithstandardques(onanswering
‣ Addnewfactstoknowledgebases
‣ SRL/AMR:handleabunchofphenomena,butmoreorlesslikesyntax++intermsofwhattheyrepresent
‣Many,manyapplica(onsandtechniques