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P r o f .l l r r s l a nM i t k o v
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rool of I{runanities, Languagesand SocialSciences
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The LexicalBasis
of SentenceProcessing
Formal,computational
and experimentalissues
Advisory Board
Christiarrlloitet (Universityof Grenoble)
John Carroll (University of Sussex,Brighton)
Eugerre Charni ak ( Brown University, Providence)
Editedby
Ilduard IIovy (lnformation Sciences
Institute,USC)
llichard Kittredge (University of Montreal)
Geoffr'eyLeech ( LancasterUniversity)
(larkrs Martin-Vicle(Rovira i Virgili Un., Thrragona)
Arrdrei l\likheev(Universityof Edinburgh)
University of Geneva
(Universityof Groningen)
John lJerlrorrrre
Nicolas I.Jicoktr,(lBM, T. J.Watson ResearchCenter)
Kcrrral( )flazer(SabanciUniversity)
University of Toronto
PaolaMerlo
SuzanneStevenson
Allarrlla rrrsey( UMISI Manchester)
I\,lolrirlrrc
Ikrlbert (Universit6de Marseille)
l(ic:lrardSlrt'oat(AT&T Labs Research,Florham Park)
Keh-YilrSu (RehaviourDesignCorp.)
l s a b c l l e ' l i ' a r r c o s( loN E S C ,L i s b o n )
'lsou
(City Universityof Hong Kong)
llenj;rrnirr
'llsujii(University
of Tokyo)
f un-iclri
Iivclyrrc'lToukernrann(Bell Laboratories,Murray Hill)
Yori<k lVilks (Universityof Shelfield)
V<rltrrne
4
'l'he
Lexical Ilasis of Sentence Processing:Formal, computational and
e x D c l i l r r e r r t iasls r r e s
L,tlitcdhy PaolaMerlo anclSuzanneStevenson
Iohn BenjaminsPublishingCompany
Amsterdam / Philadelphia
'l'he
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rrsetlin tlris publicationmeetsthe minimum requirementsof American
1',r1'er
Nari,rrrirl
sr;rrrrl,rrd
- permanenceof paperfor printed
for InformationSciences
L i b r a r yM a t e r i a l s^,N s r2 3 9 . 4 81- 9 g 4 .
Thbleof contents
Preface
vtI
words, numbers and all that: The lexicon in sentenceunderstanding
SuzanneStevensonand Paola Merlo
Part I: Fundamental issues
The lexicon in Optimality Theory
loan Bresnan
Optimality-theoretic
Library of Corrgrcss Cataloging-in-publication
Data
59
Mark lohnson
-I'he
l.r:xicalbasisol st rrterrceprocessitlg: formal, computationaland experimentalissues
/
editerlby PaolaMcrlo alrtlSuz.anne
Stevenson.
processirrg,
p. crn. (Naturall,anguage
rssN1567_9202v.4)
"'l'his volunrc <lclivesft'onrthe specialconferencesession...held
in conjunction with the
I I th Arrnual( l(.lNY( irnfcrenceon lluman Sentence
processing,
March l9-2I, 199g"_pref.
Irrcludes
bibliographical
references
and index.
l- (-lrarnrrrar,
oo'rparative and general--syntax--congresses.2.
Lexicology-C)otrgresses.
3. Pltyclroliguistics--Congresses.
4. Computational linguistics--Congresses.
I.
Merftr,Paola,1949--ll. Stevenson,Suzanne.IIL Natural Languageprocessing(Amsterdam,
Netherlands):
v.4.
P29s.t.4882002
415--<lc2l
tssN90 272 49873 (Iirrr.)/ I -sBSlI 1563 (US) (Hb; alk. paper)
@ 2(lO2* JohnRt'njanriir.s
Il.V.
Lexical Functional Grammar
39
The lexicon and the laundromat
/>
Jerry Fodor
Semanticsin the spin rycle: Competenceand performance criteria
for the creation oflexical entries
85
Amy Weinberg
Connectionist and symbolist sentenceprocessing
95
Mark Steedman
Part II: Division of labour between syntax and the lexicon
20010583
I3
No Pi111
of this brxrk rrraybc reproducedin any form, by print, photoprint, microfilm, or any
otlrcl rrreans,
rvitlrontrvrittenpermissionfrom the publisher.
(lo. .P.O.Rox36224.1020ue Amsterdam.The Netherlands
I'rrl'11511111g
ItrhrrIfenjtrrrirrs
r s. r r l r A n r e r i c a . P . ( B
J .o x 2 T 5 l g . p h i l a c l e l p hpi ae l g l l g - 0 5 l 9 . u s a
J o h r rl l c n j a r r r i rN
A computational model of the grammatical aspectsof word
recognition as supertagging
tog
Albert E. Km, Bangalore Srinivas and lohn C. Trueswell
Incrementality and lexicalism: A treebank study
VincenzoLombardo and Patrick Sturt
r37
-lahle
oI cotttcnts
Modular archi I cctu resand statisticalmechanisms:
'l'he
casellonr lexicalcategorydisambiguation
It4atthew W. Crttckerond Steffan Corley
r57
Ilncoding and storagein working memory during
sentenceconrltlcltensi<ln
Law'ie,zl.S/orye,RienkCl. Withaar, AlbertusA. Wijers,
r8r
Preface
CeesA.l. IJrttereatrd AtrrrcM.J. Paans
'['he
time course of inftrrrtration integration in sentenceprocessing
Miclmd J. Spivey,StonkaA. Fihrcva"WhitneyTabor
n,td Sdilrc(r Ajrt:l-:-tti
207
I)art III: Details of lexical entries
'l'lrc
participantsand their role
lexicals()rrrceof ttnexpressed
i u s e r r t c r r caer t r l ,l i s c o u st e u t t d e r s t a n d i n g
Gnil h4nrtrrcr,Jtnrr-l'ierreKoenig, AlissaMelinger
233
antl lJretorr Bicrr retrrte
ll.educeclt'elalivcsjudgetl hard require constraint-basedanalyses
Honn ltilip, Nliclnel K. Thnenhaus,GregoryN. Carlson,
Porrll). AllopennoortdloshuaBlatt
255
Prerlictingtlrerrraticrole assignmentsin context
Gerr\,7'. h4.Altnnrtrt
z8t
[.cxicalsernanlicsas a basisflorargument structure frequencybiases
VeredArcnrrtnnmul NeolJ. Pearlmutter
303
probabilities
Vcllr senseatrd verb sulrcategorization
Drtrtgloslloland ruul l)aniel lurafsky
325
A r r l l r o irr r d e x
347
I l r - r ni r r d e x
355
This volume derives from the special conference sessionentitled "The Lexical
Basisof sentenceProcessing:Formal and computational Issues,"held in coniunction with the 1lth Annual CUNY Conference on Human Sentenceprocessing,March 19-21, 1998.The special sessionhigtrlighted talks and posters
on current theories of the lexicon from the perspectiveof its use in sentence
understanding. Lexical influences on processing are currently a major focus
of attention in psycholinguistic studies of sentence comprehension; however,
much of the work remains isolated from the vast amount of scientific activity
on the topic of the lexicon in other subdisciplines. In organising the special
session,we felt that the time was ripe to bring together researchersfrom these
different perspectivesto exchangeideas and information that can help to inform each others'work. Participants included a multi-disciplinary slate from
theoretical linguistics, computational linguistics, and psycholinguistics,representing various theoretical framework within each of these disciplines. The
specialsessionwas quite successfulwith about 250 registrants,many of whom
do not belong to the usual CUNY crowd.
A primary motivation for the specialsessionwas that a focus of attention
on the lexicon has the potential to bring the structural and probabilistic approachesto sentenceprocessingcloser together.To gain a deeper understanding of the lexicon and its impact on processing,we need to elaborate both
the structure and the probabilistic content of lexical representations,which
together influence sentenceinterpretation. These questions bring up general
issuesin the architecture of the mind, and meet up with work in computer
science,linguistics, and philosophy on the relation between conceptual knowledge, grammatical knowledge, and statistical knowledge.
The contents of this volume reflect this range of issues from various perspectivesin the multidisciplinary study of the lexicon in languageprocessing.A
selectionof the contributors to the specialsessionwere invited to preparewritten versions of their presentationsto be included in the volume. The preparation of the final version of the papers was assistedby very careful and detailed
multiple peer reviewing. Very few of the reviewers were also contributors to
2 5 4 ( i i l l N { i r u n c re t a l .
I'carlrrrrrrrer.N., & MacDonald, M. (1992). Plausibility effects in syntactic ambiguity
of the cognitivesciencesociety
of the I4th annual conference
resoltrli,rrr.ht I'roccedings
IN.
(p. 498-'5t)i). Rloonrington,
lleichle,ll.I).,I\rllatsek,A.,Fisher,D., &Rayner,K.(1998).Towardamodelofeyemov€ment
Review,105,125-157ccrntrolirr reading.Psy'clnlogical
'f. (
arguments
and the head-complementrelation. LitrguisticInquiry,
9ti7).
I
rnplicit
I{<relrr:r; I
,l8,267-.1| O.
l{umcllrart, l)., & ortony, A. (1977). The representationof knowledge in memory. ln
of knowledge'
l{. Anrlers6rr,l{. Spiro & W. Montague(Eds.),Schooling and theaccluisition
Reducedrelativesjudged hard require
constraint-basedanalyses
Hana Filip*, Michael K. Thnenhaus+*,GregoryN. Carlson*,
PaulD. Allopenna+and JoshuaBlatt+l
99-135. I lillsdale,NJ: LawrenceErlbaumAssociates.
spccr, s.ll., & (jlifHrrr, c., Ir: (1998). Plausibility and argument structure in sentence
and Cognition,26, 965'978.
rcrrsiott.I'"lenrory
c<rrrrlrref
'lhbossi, Sl,ivcy-l(tr,Nvlton,M., McRae,K.' &Tanenhaus, M. (1994)' Semanticeffects
P.,
<r1sl,rrlar:ticarrrbiguityresolution:Evidencefcrra constraint-basedresolutionprocess.
Irr M. lr.loscovitch(Ed.), Anention and performanceXV (p.5S9-615). Hillsdale' NJ:
University of Rochester
we takeasour point of departurestevensonandMerlo's(1997)
observation
that the differencesi' the processingdifficulty of sentences
with reduced
relativeclauses(RRs)arestronglydeterminedby the inherentlexical
semanticclassof the verbsusedaspassiveparticiplesin RRs:namely,
the
unaccusative
vs.unergativeclass.our main claim is that among the linguistic
variablesresponsiblefor the relevantdifferencesa crucial role is playect
by
sema'tic variables,rather than just category-levelsyntacticcomplexity
and/or complexityassociatedwith word-internal lexicalstructure
of verbs
(seeHale and Keyser,1993).First, we observea considerable
overlapin the
distributionsof acceptabilityjudgmentsbetweensentences
with RRsbased
on unaccusative
verbsand thosebasedon unergativeverbs,and evennrore
importantly, cleargradienteffectswith respectto acceptabilityjudgments
for
both typesof sentences
that are influencedby the lexicalsemanticsof the
main verb in the matrix clause.Second,suchdatacan be successfully
motivated,if we characterizethe crucial unaccusative-unergative
distinction
in termsof thematicproto-Roleproperties(Dowty,lggg, lggl).
Third, the
linguistic analysisis consistentwith recentconstraint-basedgrammars,
most
'otably HPSG,and our co'straint_based
modelthat usesthe
integration-competition
architecture
developed
by spivey(1996)and appliecl
to reducedrelarives
by McRaeet al. (199g)and Spiveyand Tanenhaus
( 199g).
[]tlbattrl Associates,
l,arvrertce
'[iucswcll,
M., & Garnsey,S. (1994).Semanticinfluenceson parsing:Useof
1.,'larrerrlraus,
tfrerrraticr,rlc irrforrnationin syntacticambiguity resolution.]ournal of Memory and
Ln rgtt,t yt',32, 285*318.
'li'ueswcll,
J.,'lartenhaus,M., & Kello, C. (1993).Verb-specificconstraintsin sentence
elfects of lexical preferencesfrom garden-paths.Journal of
proccssirrg:Scpa111i11g
Letrning Metnoryand Cognition,19' 528-553.
ExltcrilrwrtnlPsychology:
Van Valirr, lt., & I.apolla, R. (1997). Syntax:form, meaning,and function. Cambridge:
CarnbritlgcUrriversityPless.
Van Valin, It., & Wilkins, D. (1996).The casefor'effector': caseroles, agents,and agency
(p.289& S. Thompson(Eds.),Granunaticalconstntctions
Irr M. Shibatarri
rcvisire<I.
()xford
(
Press.
)xford:
University
322).
Wif lianrs,ti. ( l9S7). Implicit arguments,the binding theory and control' Natural Language
5, I 5 1-180'
nnd Lit ryrristic'['lrctn'1',
1.
Introduction
Beginning with Bever's (1970) classicarticle, sentenceswith
reduced relative
clauses,such as The horse racedpast the barn
have
served as an important
fell,
empirical testing ground for evaluating moders of sentenceprocessing.
Bever
observed that sentenceswith reduced relative clauses are difficult
to under_
zi.6 | IanaFilip ct al
stanrl, with p('()ple often judging the sentencesto be unacceptable,because
'NP
tlrey initially assunlethat the
V PP' sequenceis a main clause.In subse,.1trent
dccatlcsone of the central controversiesrevolvedaround the question of
rvlretherstlur:trrral cor-nplexityplays a prirnary causalrole in processingdifficrrlty clf sentcrrceswith reduced relative clauses,and other sentenceswith temIior exanrple,in recentconstraint-basedmodels,the diffil)()raryarrrhirirrities.
r ulty o[ retlucctl relative clausesis argued to arise from an interaction of multiple corrstrrirrts,lnany of which are lexically-based(e.g.,MacDonald, Pearlrrrrrtterarr<lSt'itlerrberg,
1994;lbnenhaus and Trueswell,1995;Boland, 1997),
I'rrt which d,' 111;1
irrclude any factors directly attributable to intrinsic easeor
tlilficulty ol'p11r6qsci11g
syntacticstructures.lmportant empirical evidencein
approacheshas come from gradienteffectsin the
srrpportof <orrstraint-lrased
r
lilJiculty
reduced
of
relatives.For example,The eggscookedin butter
I'rocessirrlt
I'tsterldalit irtrr.sis clearly much easierto processIhan The horseracedpast the
lnru .fell. lrr corrstrastto rnced,cookedis much more often used transitively,it
is rrr<rrefr-ctlucntlyused as a passive,and eggsis a very poor Agent, but a very
g,o<lcl'l'herne
, in a cooking event.Due to such constraintsthe activeintransitive
'l'ltc
reatfing r>f
cggscookedwith butter... is lesslikely and the passiveparticiple
lil<ely.
rcaclirrgrnorc
Gradient effectsin processingdifficulty for reducedrelative
r'lauseslravebecn successfullymodeled using computational implementations
ol-nrultiple constraint models (McRae,Spivey-Knowlton and Tanenhaus,1998;
'larrcnhaus,
1998).
l i p i v e ya n c l
Ilecerrtly,Stevensonand Merlo (1997) made the important observation
tlrat the pnrcessing difliculty of sentenceswith reduced relative clauses is
strongly rlclcrrninedby the inherent lexical classof the verbs used as passive
with reducedrelativesheadedby pasI'irrticiplcsirr leduceclrelatives.Sentences
sivc participl,:s tlet'ive<lfrorn unergative2verbs are "all mostly or completely
urracce
ptalrlc"(p. 355).In particular,manner of motion verbs"lead to a severe
liirrclerrlrilth in tlre l{R construction" (p. 353), as is shown in Stevensonand
lvlerlo's(p. l!' j) exarnples,hererepeatedin (1). In contrast,"unaccusativeRRs
;tr.eall cottrl'lclclyacceptable
or only slightlydegraded"(P. 355).Stevensonand
Merlo'scxarrrples
are repeatedherein (2):
'l'lre
ir.
clippersailedto Portugalcarrieda crewof eight.
'l'lre
b.
troops rnarchedacrossthe fieldsall day resentedthe general.
'l'he
nrodelplanet rotatedon the metal axis fell offthe stanc.
c.
'l'lre
dog walkedin the park washavinga good time.
tl.
'l'[re
(2) a.
rvitchrneltedin the Wizard of Oz wasplayedby a famousactress.
'l'lre
genesmutatetl in the experimentwere usedin a vaccine.
b.
( l)
Reducedrelativesjudged hard requireconstraint-based
analyses
c.
d.
The oil poured acrossthe road made driving treacherous.
The picture rotated 90 degreeswas easyto print.
stevensonand Merlo propose that the unergative/unaccusative
clifferencecan
be explained using Hale and Keyser's (r9g3) syntax-in-rhe-rexicon
model,
couched within Government and Binding Theory in which
important aspects
of lexical-conceptualstructure are mirrored by syntactic
structures within the
lexicon. unergative verbs are syntacticallycharacterized(among
other things)
by having an external argument, but no direct internul
u.gu--"nt, while unaccusativeverbs have no external argument, and a direct
inon-clausat, non_
PP) internal argument. Due to such lexical properties,
transitive and passive structures, including those in reduced relative clauses,
which are derived
from inherently unergative verbs are significantly more
complex than those
derived from unaccusative verbs "in terms of number
of ,rod., u.ra ,rrrr_
ber of binding relations, and in having the embedded comprement
structure,,
(stevenson and Merlo, 1997:364).when these
linguistic assumptions are implemented in Stevenson's(r994a, b) competitive attachment
parser, a kind
of symbolic/connectionist hybrid, it turns out that the parser
cannot activate
the structure needed for a grammatical analysis of reduced
relatives headed
by passiveparticiples with unergative verbs, "becauseof its
limited ability to
project empty nodes and to bind them in the structure" (Stevenson
and Merlo,
1997:397).Hence, the parser is viewed as confirming the earlierjudgment
data,
namely that there are "sharp distinctions between unergative
RR llauses and
RR clauseswith other verbs" (p. 396).
In contrast to previous structural theories which attribute
the difficulty
of reduced relatives solely to category-level syntactic complexity
differences,
stevenson and Merlo propose that rexical constraints pray
a central role in
determining the processingdifficulty of reduced relative
clauses.However. in
contrast to constraint-basedmodels, they argue that differences
among crasses
of lexical items are due to differencesin structural complexity
associatedwith
their lexical structures.They argue that reduced relatives
with participles based
on unergative verbs are uniformly difficult to process,regardless
of factors such
as frequency and plausibility, that is, "structural compiexity
alone can cause
failure to interpret a sentence,evenwhen all other factors
would help its correct
interpretation" (Stevensonand Merlo, 1997:392).
If correct' Stevensonand Merro's claims would have a number
of important implications for theories of sentenceprocessing.First,
they would provide
the clearestevidenceto date for structural complexity
effectsin sentenceprocessing,due to the internal syntactic structure of words,
thus helping to resolve
2\
j8
Reducedrelativesjudged hard requireconstraint-basedanalyses 259
Ilarra Filip et al.
cotrtroversyinthe freld.Second,since there are both syntaca lolrg-starrdilrg
distinction,Stevenson
asPects
of the unergativelunaccusative
lic and serrrarrlit,l
alr,l Melkr's rcstrllsrvottlclstrongly support an approach in which syntacticcorrcl;rlcsof scrrlrrrticdistinctionsplay the primary causalrole in accountingfor
vali;rtion in processirtgldifficulty.
ln this r'lrirplql rve evaluate Stevensonand Merlo's claims in light of ad<liti,rnalcrnpirical data and modeling within a constraint-basedframework.
Sc,.tion 2 prcserrtsthe resultsof a questionnairestudy which replicatesStevenson irncl Merlris fincling that reduced relativeswith passiveparticiples derived
frorn uncrgative verbs are, as a class,more difficult than reduced relativeswith
passiveparticiples basedon uuaccusativeverbs.However,the resultsalso show
that there is a consitlerableoverlap in the distributions of acceptabilityjudgdifliculty, as would be expectedon a constraint-basedacnrents atrtl 1'rrrrsing
count. Sectiotr3 shorvsthat the processingdifficulty that is due to the unergadifferencefalls out of a computationalimplementation of a
tivc/unaccusativc
corrstraint-lrasctlmodel, using only those constraints that recent constraintb;rsccltlteoristsltirveclailned account for processingdifferencesamong reduced
rclativcs (Macl)onalcl et al., 1994; Thnenhausand Trueswell, 1995). Thus the
differencedoes not require appeal to structural comutrcrgative/rrtact:ttsative
plcxity differelrces.In section 4, we argue that a semantic approach based on
tltclnatic roles presents a promising alternative to the syntax-in-the-lexicon
'l'lrc
tlrentatic properties, which characterizethe two fuzzy cluster
apgrroach.
c()n('eplsProto-AgerrtanclProto-Patient(Dowty, 1988,1991),can accountfor
a y,rcatdeal ol'pr'ocessingdifferencesbetween sentenceswith reduced relative
verbs,
[irserlotr tutergativeverbs,on the one hand, and On unaccusative
cl:rrrses
qrr thc ollrer lrarrd.One advantageof this novel way of looking at the gardenp;rtlr phcrrorrcrrorris that it allows us to understandthe similaritiesbetween
[lrr.st.two lypcs of sentencesin exhibiting clear gradient effects with respect
kr acceptabilityjtrcignrentsand parsing difficulty that are influenced by the
lcxit.alsernanlicsof the mair.rverb in the matrix clause.The influenceof the
rrr;rirrpretlicirlr:itr a sentenceon the magnitudeof the garden-patheffecthas so
firl y.oncrrrrrroliceclanelit is problematic for structure-basedaccountsthat assrrn'e cilhcr <irtcgory-levelsyntactic complexity and/or complexity associated
willr word-irrlerttallexicalstructure of verbs.We also show that a constraintthesesemanticnotions can be naturally embedbirs"dapl rcluchirrcorprorating
dcrl withiu rccenl collstraint-basedapproachesto grammatical representation'
Wc conclucleby tlescribing a rating study that showsthe effect of the main verb
on the processirrgdifficulty of whole sentenceswith reduced relative clauses,as
is predictcdby rttrr linguisticanalysis.
2.
Gradient effects
we observed that sentenceswith reduced relatives based on unergative verbs,
including manner of motion of verbs, manifest a considerabledegreeof variability in acceptability,and, in fact, perfectly acceptablesentencesof this type
are easy to find. Examples are given in (3). At the same time, some reduced
relatives with unaccusative verbs are relatively hard, such as those in (4).
(3)
a.
b.
c.
d.
The victims rushedto the emergencyroom died shortly after arrival.
The pig rolled in the mud was very huppy.
The Great Dane walked in the park was wearing a choke collar.
The prisoners paraded past the mob were later executed.a
(4)
a.
b.
c.
d.
The theatredarkenedfor the movie frightenedsomepreschoolers.
The Klingon disintegrated during the battle had launched a rocket.
The solution crystallizedin the oven burned a hole into the petri dish.
The plasterhardenedin the oven crackedwith loud popping sounds.
In a questionnaire study we had twenty-four University of Rochester undergraduates recruited in introductory courses use a five point scale (l = very
easy,5 = very difficult) to rate the difficulty of a mix of sentencesthat included
reduced relative clauseswith inherently unaccusative and unergative verbs, as
well as transitive and passivemain clausesentencesusing the same verbs. The
full set of materials used in the rating studies are availableby requestfrom either of the first two authors. Table I presentsthe mean ratings. There was a
significanteffectof constructiontype, Fl(1,23)=62.00,p<.01; F2(2,32)=82.O2,
p<.01. Reducedrelativeswere significantly harder than passivesor transitives,
regardlessof verb type (all planned comparisonswere significant at p<.01). We
replicated Stevenson and Merlo's finding that sentenceswith reduced relatives
headed by passiveparticiples based on unergative verbs are harder to process
than sentenceswith reduced relativesheaded by participles derived from unaccusative verbs. For reduced relatives with passive participles derived from
unaccusative verbs, the mean was 2.95; and for those with unergative verbs,
the mean was 3.45. This difference was reliable in the analysis by subjects,
F(1,23)=5.51, p<.05. However, there was substantial overlap in the distributions, and in fact the difference between the unaccusativesand unergatives was
only marginally reliable in an item analysis,F(1,32;=3.15, p=.085. Four of the
eighteen unergative verbs used as passiveparticiples in reduced relatives were
rated as yielding sentenceswith reduced relatives judged easier than the mean
rating for sentenceswith reduced relativesbased on unaccusativeverbs. The
sentenceswith these verbs are in (3) above. ln addition, some sentenceswith
Reducedrelativesjudged hard require constraint-basedanalyses 26
16o I larral;ilip et al
'lrrlrle
l . fr r r l l i c t<l l i l l i c u l t yo f r e d u c e drelatives
Transitive
AA
.----f
| tl
o ooo
Trans
Pass
2.95
1.63
1.60
3.45
',t.52
Class
O Urracr:rrsatives
A [JnFrqatives
o oo
A
A
o
ooooo
Interpretive
Nodes
\lHl
t=t
'l:
1.81
re(luce(lr-elativesheadedlry passiveparticiplesderived from unaccusativeverbs
\vcrerate(las nl()r'eclifficult than the mean rating for sentenceswith unergativebaseclrcclucc<llelatives(3.45). Six of the sixteenunaccusativeverbs fell into this
the sentences
in (4).
cntegory,inc:lnclirrg
fb surnrrrarize,the ratings showedthat sentenceswithunergative-basedretlrrceclrelativcs\vereon the whole more difficult to processthan sentenceswith
rrrraccusrlivr.'heserl
reclucedrelatives,but also that there was a considerable
rlt'grccof'ovcrlap betweenthesetwo types of sentenceswith respectto the pro-
Intransitive
.l ^l
I lt ^: ll
lol
u
N
t(ol
t-l
@) l@)
E
o
F
cessingdilli<'rrlty.'l'heoverlapin the distributionsand the continuum of difficulty is pr oltlt'nrrrlicl'or an account in which the inherent structural complexity
vo bs preclicts"sharp distinctions between unergativeRR clauses
oI nner11:rtivt'
autl llll cfarrscsrvith other verbs" (Stevensonand Merlo, 1997:396).They do
definitive evidenceagainstsuch a proposal, however,berrot, holvcvcr',1rr.,rvi<le
cirusenleasurt'rncrrtel'ror or other differencesamong materials could lead to
ovcrlaf in tlrc tlirtaevenif the underlyingdistributionsdid not overlap.
j.
model
A conslrairrt-trasecl
We irnplernctrtetla constraint-basedmodel using the integration-competition
arcfiitccture tlevelopedby Michael Spivey and applied to reduced relativesby
McRae et al. ( 1998) ancl Spivey and Thnenhaus( 1998). In this model alternative syntacticslrLrctrlrescornpetewithin a probability spacewith multiple conslraints prrovidirrgprobabilistic evidencefor the alternatives.This model is not
a firlly ilrrplerncntctl parser;rather, it is an architecturefor predicting the diffiapculty of arnbiguityresolutionusingprinciplescommon to constraint-based
'l'he
qrrestionwe addressedwas whether an unergative/unaccusative
prrraches.
Figure l. The Integrationand competition model usedin the current simulations.
Eachvertical rectanglerepresentsthe input ofa particular constraint.The horizontal
rectangalrepresentsthe output of the model at any point in time for the three integration nodes for the embeddedclause:the active transitive,active intransitive and
passivein a reducedrelative.Constraintsfor tense,voice,transitivity and thematic fit
were introduced at the embeddedverb. The PP constraint was introduced after the
model completedrycles(i.e., until the dynamic criterion was reached)for eachinput
at the embeddedphrase.Similarly,the main verb constraintwas introducedafter processingwascompletedfor the PP,The weightsshown are thosethat wereusedwhen a
constraintwasfirst introduced,i.e.,beforenormalizationat the next input.
difference would fall out of such a model using just those constraints that have
been previously identified in the constraint-based literature.
Figure I presentsa schematic representation of the model. In the model,
three constructions competed, beginning with the first verb in a sentencewith
a reduced relative clause:NP V(-ed) PP V. The constructions were: active tran-
iz
Reducedrelativesjudged hard require constraint-basedanalyses z(
I I;rrralrilip cl al.
McRae and colleagues(cf. McRae et al., 1998). Ratings were collected using a
five point scale.Questions we used are here exemplified using the verb melt as
'How
an example:
common is it for ice to melt someone or something?' (Active Transitive),'How common is it for ice to melt?' (Active intransitive),'How
common is it for ice to be melted by someone or something?' (Passivein RR).
We tested the model on six unergative verbs, danced, raced, paraded, rushed,
mqrched, hurried, and on four unaccusative verbs, dissolved,cracked,hardened
and melted. This small subset of verbs represents those for which we had corpus counts, difficulty ratings and ratings for thematic fit. Table 2 presents the
biasesused in the model for each of the four constraints that applied at tbe -ed
and passivein a reducedrelative.The full passivewas
sitive,activeirrlrirttsitive,
-rrl
verb form becauseof the absenceof a preceding copula,
ruletl out- at the
a n , l t h u s\ \ ' a sl r o t i n c l t t c l e d .
J'|e conslrairrtsused were those identified by MacDonald and colleagues
(e.g., MircDr)nirl(let al. (199a)) and by Tanenhausand his colleagues(e.g.,
'l-t-tteswell,
'[hncnhaus
1995).The followingfour constraints came into play
anrl
at tlre ,erl verb firrtn: ( | ) The frequencywith which a verb was used transitively
or intransitivcly; (2) the frequenry with which it was used in tensedvs. tenseless constnrctions; (3) the frequency with which the -ed verb form was used
in rhe passiveand aclive voice, and (4) the plausibility with which the first NP
could fugcti1rtras sttt)jectof an active transitive, subject of an intransitive, and
subject of a prrssive("thernatic fit"). An additional frequency constraint came
verb form.
Table2.
into play at lhe I'l), atrclanother at the main verb.
In the intcgration-cotnpetition model, eachconstraint provides probabilistic:strpport for the sytrtacticalternatives.The normalized bias on the constraint
is rrrrrltiplieclhy the weight assignedto the constraint. The weights of all the
corrstraiutsapplyl"* at a given input are normalized so that they sum to 1.0.
'l'lrr.
rnotlclrvorlls iu tlrreesteps.First the biasesare multiplied by the weightsto
Word
delt.rnrinellrc cvirleltce(activation)eachprovidesin support of the competing
irrtr.rplelatiorr(irrteglation)nodes.Activations are summed at each integratiorr rrotlc. Scr,rrrtl,feedtrackto the constraints is provided by multiplying the
prolrx[rililyol'crrlr integrationnode byits weight and adding that value to its
'l
prr.viousllias. lrinl, the biasesfor eachconstraintare then renormalized.The
rrr,,,lclcontilrncscycling until a designatedcriterion; the criterion is lowered
alter each cycle. (lr0r cletails,see McRae et al., 1998; spivey and Tanenhaus,
l9,r[].) Wlrerr lhe criteriolr is reached,the model moves onto the next region
q[ tlrc text, in tlris casethe PP.The new constraintprovided at the PR namely,
strorrg evi<lerrcef<rr either an intransitive or a passiYe'was assigneda weight
of 1.0,follorvirrgthe procedureused in McRae et al. (1998).All of the weights
lvert- tfiep relorrrraliz.ed,resulting in a weight of .5 for the PP and '125 for
equal weiglrt ol'.25. Biasesfor transitiviry tense, and voice were determined
flrrtrr c<tr'pusirrrall'sesusing the ACLiDCI corPus' comprising the Brown corpus rrrcl 64 rrrilliorr rvortls of the Wall Street Journal that were kindly provided
to us lry Paola N4erloancl SuzanneStevenson.The biasesfor thematic fit were
{etr:r.urinetllry typicality ratings collected using the procedure developed by
Bias
lntransitive
RR
Tense
Thematic Fit
Transitivity
Voice
0.31
0.12
0.37
0.41
0.31
0.38
0.45
0.41
0.38
0.50
0.18
0.19
Danced
Tense
Thematic Fit
Transitivity
Voice
0.40
0.2r
0.15
0.43
040
0.s6
0.77
0.43
0.21
o.24
0.08
0 .l 4
Dissolved
Tense
Thematic Fit
Transitivity
Voice
0.l6
0.17
0.50
o.2l
0.16
0.43
0.25
o.2l
0.68
0.41
0.25
0.58
Hardened
Tense
Thematic Fit
Tiansitivity
Voice
Tense
Thematic Fit
Transitivity
Voice
0.05
0.21
0.43
o.23
0.32
0.3t
0.39
0.34
0.45
0.22
0.06
0.49
0.15
0.05
0.49
0.36
o.23
0.32
0.35
0.42
o.34
0.45
0.43
0.91
0.49
0 .l 5
0.91
0.30
0.21
0.55
0.37
0.34
0 .l 9
0.31
0.09
0.35
0.03
0.01
0.71
Marched
Tense
Thematic Fit
Transitivity
Voice
Melted
Tense
I
i
I
Transitive
Cracked
Hurried
tense,voice, tlretnatic fit antl transitivity. The same procedure for normalizing
weights was firll<xvedwhetr the model moved on to the main verb'
IJecauserve tlicl 6qt have an independently motivated way of setting the
weiglrts glt the lirur constraints at the -ed verb form, we assignedeach an
Constraint
Reducedrelativesjudged hard requirc constraint-basedanalyses 2,65
t 4 I h r r ; rI ; i l i l ' c ;l r l
'lhlrlc (corrtitrtttrl)
2.
W<rlrl
( onstt'airrt
Transitive
few,'lry
Mclrcd
Wilth
'l
l r c r r r a tFi ci t
'li
rrrisitivity
Voice
'l
i'rrse
'flrenratic
Fit
ltansitivity
Parirrled
Vrice
'l
t'rrse
'l'hernatic
l { a <r ' d
Itrslred
0.16
0.34
0.31
0.28
0.t5
0.35
0.34
0.28
0.28
0.15
o.32
0.49
0.28
$.25
0.28
0.55
0.31
(r'r<
Fit
0.26
liarrsitivity
0.30
0.3I
\i rice
'l
Bias
lntransitive
i'rrsc
I l r r r r r a l ilcr i t
li;rrrsitivity
0.50
0.10
0.05
\ / rr i c e
li'rrse
0.50
0.40
l l r c r r r a t iFc i t
'li
ansitivity
\/oice
0.26
0 .l 4
0.44
Q.49
0.50
0.45
0.93
0.50
0.40
0.33
0.80
0.44
RR
0.53
o.t7
0.44
0.71
0.33
0.17
0.44
0.s0
0.46
0.15
0.39
0.01
0.45
0.02
0.01
0.20
0.41
0.07
0.t2
I
I
,
i
'Jhble
2, unergativeverbs tend to be used more often than
As crrn be seerrfrrlrrr
vetlrsitt intransitiveconstructionsand lessoften as passives'For
runrccusative
of an
turergativeverlrs these factors mean that the active intransitive reading
'Nl,
V(-erJ) I)I)' li.agtlent will be more strongly biased relative to the reduced
rel:rtiveclattsclertlitr g.
In or{cr to cv;rlrratet|e output of the model, we considered three measures.'l'[e {irst was the total number of cyclesuntil the criterion was reached
at
f
at tlre ruaiu vellr (cyclesat the -ed verb form, + cyclesat the PR cycles
the rnain verb).'l'lreseconclwas the probabilityassignedto the reducedrelative
take
structure at thc rrrail vertr. The third was the number of rycles it would
verb'
main
the
the rno{el to assigrrthe reclucedrelative a probability of .9 aI
lVc asstrrnedllrlt each of these lneasuresshould correlate with the difficulty
Ill three measurespredictedthat as a classreducedrelatives
ol'tlre scntcrrt.rl.
deriveclfrom unergativeverbs would be more diffiwitlr passivePat.ticiPles
cglt tfiarrrc.lrr,,',1relativeswith passiveparticiplesderivedfrom unacccusative
vetbs:firr total rttttrtberof cycles,t(9)=3'16' P<'01; for probability at the main
all
verlr t(9)=1.95, p- .()2;anclfor cyclesto a criterion of '9, t(9;=Z '99' p<'02'
teststwo-tailed. The model also correctly predicted some gradient effects.For
example, the reduced relative beginning with The witch melted.. . was correctly
predicted to be harder than the reduced relative beginning with The jewelry
melted... . In addition, the reduced relative with paraded was predicted to be
easier than the reduced relatives vnth danced, raced or marched. However. The
victims rushed to the hospital died was incorrectly predicted to be quite difficult
even though it was rated as fairly easyby subjects.
It is important to note that the model we presentedis incomplete in important ways. There are constraints that are not included and as a result the
model generally overestimates the availability of the reduced relative analysis. Moreover, we were working with only a few verbs for which we had data.
Nonetheless,it is clearthat the processingdistinction betweenreduced relatives
headed by passiveparticiples derived from unergatives and unaccusativesfalls
out of a small set of constraints, primarily verb-based frequencies,that have
been independently argued for by proponents of constraint-basedmodels.
In the light of the results we reachedso far, a proponent of the syntax-inthe-lexicon approach might appealto two types of counterarguments.The first
might be that frequencies reflect the unergative/unaccusative distinction; however, the structural complexity associatedwith the lexical structures of these
two classesof verbs results in those frequencies and actually plays the causal
role (but cf. MacDonald, 1997). The second argument is that the syntax-inthe-lexicon approach implemented in stevenson'sparser is superior becauseit
presupposesa full-fledged linguistic theory, namely, Government and Binding
Theory, whereasthe constraint-basedapproach is not supported by independent Iinguistic assumptions in a similar way. In the next two sections we address these issuesin turn. First, we explore and motivate the claim that among
the linguistic variablesresponsiblefor the processingdistinction a crucial role
is played by semantic variables, rather than just syntactic variables. Second,
we show that the ideas implemented within our simple model are broadly
consistentwith recent constraint-basedgrammars, most notably HPSG.
4.
{
t:
The linguistic basis of unaccusative/unergative distinction
in processing
Our primary observation,and one that has so far gone unnoticed, is that both
types of sentenceswith reduced relatives exhibit similar gradient effects in acceptability judgments that are crucially influenced by the lexical semanticsof
the main verb in a matrix clause.To put it in the simplest terms, the fewer
Reducedrelativesjudged hard require constraint-basedanalyses 267
6 6 F l a r r aF i l i P e t a l
argument position is unfilled, and it can be filled by an 'external cause' argument, when they are used transitively. This does not hold for unergative verbs,
because they already have one external subject argument. By this test,yellow
in (lOa) and solidifu in (lOb) are unergative,while hardenin (lOc) and.yellow
in (10d) are unaccusative.(Examplesin (9) and (10) are taken from stevenson
and Merlo, 1997:365.)
asagelt-lil<e pr()l)clties ancl the more patient-like properties the main verb
clause
relative
reduced
a
with
sentence
the easierthe whole
sigls to its srrfijet:1,
isludgctl.'l'his itlea rvill be discussedin detail in Section4.2, but let us illustrate
it here witlr a fcrv exarlples. In (5a) the su[ject of complained,the patients,is
is
a volitional agclrl in the denoted event, and we seethat the whole sentence
undergoes
lessaccepta$lellras (5b) with tlied as the main verb, whose subject
a clrangeo[ statc.A sinrilarcontrastcan be found in (6):
(s)
'f 'lre
to the nurse'
a.
lratientsrylhgd to the emergencytoom#com,lained
'l'f
died.
room
emergency
to
the
rc patientsrushed
lr'
(6)
a.
b'
(e) a. #The candy caramelisedin an hour burned.
b. #The wax solidified into abstract shapesmelted.
c , #The paper yellowed in the sun shrank.
( r 0 ) a . #The chain-smoker yellowed the papers.
b. #The sculptor solidified the wax.
l'frc ( ireat l)ane walkedin the park#tug:rcdat the leash'
'lrc (
ilert I)anewalked inthe parkworea chokecollar'
f
c. The sculptor hardened the wax.
d. The sun yellowed the paper.
Sirrrilarlyirt rr',lrrceclrelativeswith passiveparticiplesderived from unaccus a t i v c v t ' r ' l r s , s r r r l rtal nsr k e n e r i i n ( 7 ) , w e s e e t h a t t h e u s e o f f r i g h t e n e d a s o p p o s e d
irr tlre rnatlix clauseis correlatedwith a differencein the acceptability
t, srrtelletl
'I'l're
reasonis that frightened,but not smelled,presents
tr{'tlrc rvlrrrlcsqrrlettce.
in
tlrc strlrjcct tlrc thentreas the causeof the change of the psychologicalstate
are
examples
similar
Other
preschoolers.
tlrc refcrent ol'the direct obiectsome
g i v e ni r t ( t t ) :
(7)
a.
b.
(S) a.
b.
'l'lrc
#frightenedsomepreschoolers'
theatre darkened for the movie
thcatredarkenedfor the movie smelleQlikepopcorn.
'l'[rc
'l'hc
getresn.rutatedin the experiment#attackedtheirhost'
'l'lre
genesmutated in the experimentwereusedin a new vaccine.
(5)-(8) resist
N{ost irnportailtly, different degreesofacceptability observed in
in the
couched
arr explanatirrrrin structure-basedterms aSwell as explanations
that the
syrrtax-irr-thc-lexiconapproach of Stevensonand Merlo (1997). Recall
inherently
by
headed
relatives
reduced
with
lirtter pretlict tlrat n/l sentences
'rrersrrtivcv<'rl'sare predictedto pose'sharp difficulty'(p. 392) for an intergrammatical analysisbythe parser.In
l)rclcr, a'{ tlrci,car'rot [e assigneda
reduced relativesthat are not easyto
.r.tfer lrr ifcroulrl firr r.rnaccusative-based
as thosein (9), Stevensonand Merlo resortto the semanticdisirrterprct,srr<.lr
'external
'itrternal
causation' (see I-evin and
causation' and
tirrctiolt lrt.lrvr.crr
are unergative.According
they
that
I lov:rv, 1995:210-211)to argue
ILaplratrrnrt
'internal
causation' in
trr tlrenr, vcrlrs like (orotnelise,sotidify and yellow entail
from
tlrcir serlatrtic <lescription,a feature that distinguishesunergative verbs
unac(see
Since
ibid.).
caused'
Irlaccusativeorres,the latter being'externally
cusativeverlrs ltave one internal direct object argument' the external subject
i
I
i
ii
,!l
The problem with this test is that unergative verbs, including agentive manner
of motion verbs, when used transitively require their subject argument to be
an Agent: cp. *The explosionjumped the horse vs. The jockey jumped the horse.
(This observation was made by cruse, 1972;lackendoff, L972;Levin ancl
Rappaport Hovav, 1995; seealso stevenson and Merlo, 1997:357and footnote
4
below.) This inconsistency clearly indicates that a test based on the possibility
of the overt expression of an Agent argument cannot be the right diagnostic
for deciding the membership of verbs in the unaccusative and unergative class.
The main source of confusion stems here from correlating'external causation,
'possibility
and
of an overt expression of an external agent', on the one hand,
'internal
'prohibition
and
causation' and
against an overt expression of an external agent',on the other hand. what is lacking is a precise characterization of
'internal
the notions
causation' and 'external causation', introduced by Levin
and Rappaport Hovav (1995), and the motivation for the correlation of these
semantic notions with the syntactic structures associatedwith unergative and
unaccusativeverbs.Moreover, ( l0a) is claimed to be lessacceptablethan ( lOd),
becauseits subject referent may be intentionally involved in the denoted event,
while in (l0d) the denoted changeof stateis "indirectlybrought about by some
natural force" (p. 365). However, it is not shown how such a fine-grained distinction between '(volitional) Agent'and'natural force',and the suggesteddifference in acceptability judgments, can be viewed as being correlated with the
external subject argument in the caseof unergative verbs, and with the internal
object argument in the caseof unaccusative verbs.
Reducedrelativesjudged hard requireconstraint_based
analyses z
2 6 8 I l a n a l r i l i pt t r r l
'l'he
faci lh;rl Slevettsonand Merlo do resort to rather subtle semantic crileria irr orcler.to accoLlntfor difficult casesis instructive, becauseit shows that
explarrationsirr tenns of categoricaldifferencesbetween syntactic configurations in tlre lexicqrr are insufficient. Indeed, one may ask to what extent syntactic lhc:torsal e necessaryin addition to semanticones in order to account for
the garden-1)atlrl)henomenon. If we focus on the differential semanticsof the
vertrsirt tlrc rrr:ttetialtliscussedhere' we can begin to acount for the overlapol'setrtences
with reducedrelativesaswell as the greatdeal of
Iring rlistrilrrrtirrtt
vrrrialrilityrvillr r espectto how good or bad they arejudged to be, leavingopen
llrc tprcs(iotr trl.rvltatrole, if any,a word-internal syntacticdifferencesare left to
pl:ry.\Vc nr)w lurll tcl characterizingthose semanticconstraints more precisely'
4 . r . ' l ' l r e n r a t i ,l.' r o t o - l l o l e s
'l'he
idea tlrat ar.gurnentpositions ofverbs are associatedwith certain "thematic
1rles" (()asclltrles,CaseRelations)such asAgent,Patient,Instrument, and so
forth, has rcccived varying characterizationsin the linguistic literature' Here,
however,wc lirllorv the analysisof David Dowty (1988, 1991)' who proposes
tlrat the only tlrcrnaticrolesare two clusterconcePts,Proto-Agentand ProtoPaticr-rt,each rharacterizeclby a set of verbal entailments, given in (11) (see
Dowty, 199| : i,t72)." IAl n argument of a verb may bear either of the two proto(or |otlr) t11valying {egrees,according to the number of entailments of
r<.rles
cach kind lhc verb givesit" (Dowty, l99l 547).
:
(11) a(tlrrilptllC"roperties for the A
state
or
the
event
in
a. volitional iuvolvement
r erception)
h . ( ( ' n t i c n c(ea r r d / o p
(:. c;rrrsittgalt evelltor changeof statein anotherparticipant
(1. rtoveltlettt (relativeto the position of anotherparticipant)
( c. t eferetttexistsindependentof action of verb)
(irlrtr ilttrtirlSpropertiesfor the PatientProto-Role:
charrgeo[ state
trrrrlergoes
h le m e
lr. i r r c r c r r r e n t a
.;rrrsally
allectedby anotherparticipant
C.
(l.
stirliorraryrelativeto movementof anotherparticipant
(c. 'l()esrtot existindependentlyof the event'or not at all)
il.
The Argument SelectionPrinciple determines the direct associationof clusters
of Proto-Agent and Proto-Patient properties with grammatical relations in a
many-to-one fashion:
(LZ) fugument SelectionPrinciple
(Dowty I99l:576)
In predicates with grammatical subject and object, the argument for which the
predicateentails the greatestnumber of proto-Agent properties will be lexical_
ized as the subject of the predicate; the argument having the greatest number
of Proto-Patient properties will be lexicalizedas the direct obiect.
4.2 Compatibility between subjects in sentences with reduced
relative clauses
In reviewing the contrasts found in examples,such as (5)-(g), it appearsthat
the following is a reasonable description of one effect of the main verb on a
reduced relative clause:
(13) Hypothesis
The acceptabilityof sentenceswith reduced relative clauses,headedby passive
participles derived from unergative and unaccusative verbs, increaseswhen the
passiveparticiple and the main verb of a matrix clauseassigntheir subiect-Nps
more Proto-Patient,and fewer Proto-Agent, properties.
The intuition behind the hypothesis ( l3) is that sentencesare easierto in_
terpret when there is an internal coherenceamong the interpretations of their
constituents.one way this coherencecan be achievedis in terms of compatible
assignmentsof thematic properties to different Np arguments that are associated with one and the sameparticipant in the domain of discourse.In sentences
with a reduced relative clause the internal coherence depends in part on how
well the thematic make up of the subject Np in the matrix clause matches the
thematic make up of the PRo-subject of the reduced relative clause:namely,
the passive participle in the reduced relative requires that its pRo subject be
a"very good" Patient. Let us take (la) #The horse raced pastthe barn
felt. At
the point wlten raced is processed,the preferred syntactic-semanticpattern
is that of the main clause with an agentive subject-Np. However, when
/e// is
processed,raced must be understood instead as a passiveparticiple. passive
participles typically presupposethe existenceof corresponding active transitive verbs whose subjects correspond to active direct objects (seesag and wasow, 1997:164, for example; however, passivesubjects do not always correspond to active direct objects,seeZwicky, l9g7; postal, 19g6, and others). Let
70
Reducedrelativesjudged hard require constraint-basedanalyses 2.,
lIan.r Fil(r et al
properties by the verb racedin its
rrs frow lcrok at the assignmentof thematic
(lexicalcausative)use. ('PA standsfor
irrtr.nsitive(rrrr.gativei and transitive
'PP'
f o r P r o t o - P a t i e not n e s ' )
lie
| ) r o t o - A p , t ' nI II1 1 1 r e
t sa n d
( | 4)
other participant', and given that thehorse in (15) is a sentient being with a
(potentially) certain volitional involvement in the racing event, 'movement'
can be here taken as the Proto-Agent property. (This is not uncontroversial.
However, feII does not assign clear Proto-Patient properties to its subject ei'undergoes
ther. A candidate might be
a changeof state',but here it would not
mean a permanent change,rather just a change in bodily posture, and hence
ultimately'movement'.) Hence, the thematic make up of the subject Np in the
matrix clausedoes not match the thematic constraint of the reduced relative
clause which requires that its PRO subject be a "very good" patient.
past thebarn'
'l'lrt'
lrorscI,,\C):D pastthe barn' The rider MCED the horte
I
!r\
( I vt'litiotr)
Iscnti{lllce
-l ilt()v('lllelrt
I
PP
PA and
PA
causallY
+
(+
volition)
+ volition
+ sentience affected
+ sentience
+ causing change + movement
"usual" transitive in that it semantiA t.ausativclirlrrr of au ttnergativeis not a
prototypical transitives
cally cleparts[Krrrr prototypical transitives.Intuitively,
'billiard
ball model" as Langacker(1986) calls
can be utrclcrsto.d in term.sof a
an asymmetric and unidiit, which involvt's tlvo participants that interact in
(possibly
,r'. .rfih.n', is directly affectedby some action
rectiorralrviry,rvlrereLry
instigated or causedby the
involving tttovcttteltt, cotltact, effect, and the like)
the direct object has many
other participunt. h'r l)owty's terms, tl-rismeans that
pr'tolPatie't (a.cl a few Proto-Agent) proPerties, and the subject has many
A typical unergative verb
Proto-Agertt (arrd a ferv Proto-Patient) properties'
becauseits
usecltrarrsirivelycloesDot lrt the semanticsof a transitive PrototyPe,
(14)
example
our
"good" Agent: in
dilcct object hrrsa therl-raticmake up of a
of
the
to the object
tlre strbject tlrehorse<;f the intran sitiveraced corresponds
proto-Agent properties. At the same, tfte
trrrrsiti'e rtrrcrl a'rd tlrcy share three
affected'by the transitive
hr|..seis assigrretlorre lrroto-Patient property'causally
use of unergativeverbs
rncrd.,l'ltealvkrvardnessoften related to the transitive
these two different roles or
tDaybe sccil ils slcrrrnrirrgfrorn having to reconcile
(an Agent-like and a Patient-like) on one and the
trvo cli{lererrtl''-'r-sirectivJs
This carries over to passarne|articiParrt in the denoteclcomplex eventuality.
verbs' The reason is that a
siuc particif ies <letivetlfrom inherently unergative
to have a high number of
prototypicrrl |assive cQnstructionrequiresits subject
an unergative.verbsupplies
Pflrto-Patierrt prrrperties,yet a passiveparticiple of
properties,given that
a subject argunrctrt that carriesa number of Proto-Agent
verb (The rider raced
it correspondsto the direct object of an active transitive
of the active intransitive
tlre lrorse),rvhiclrin ttlrn corresPondsto the subject
in (15) we seethat the
verb (The horse rnt:ed).Toreturn to our lead example'
as the
plto subject of the passiveparticiple has the same thematic properties
a "good" Patient' The main
correspouditlg actrveobject in (14), hence it is not
verbfellassignstheproperty.movement'toitssubjectthehorse.Insofaras
'movement relative to the position of anthis can bc irrtcrprctetl itr terms of
(15) Thehorsei
I
[< PROi > RACED past the barn] fell.
I
PA
PA and
+ movement (+ volition)
PP
+ causally affected
a sentience
+ movement
lf, on the other hand, the main verb of a matrix clauseassignsProto-patient,
rather than Proto-Agent, property (or properties) to its subject, the magnitude of the garden path effect is diminished, as (16) shows: the subject of
died is clearly a "better" Patient then the subject of fell, as it is entailed to undergo a permanent changeof state.Hence, (16) is somewhat easierto interpret
than (15).
(16) Thehorsei
I
I<PROi > RACED pastthe barn] died.
I
I
PP
PA and
PP
+ undergoeschange (+ volition) + causally affected
of state
* sentience
+ movement
of course,not all transitive and passiveusesof inherently unergativeverbs are
odd. Other factors, such as expectations related to the occurrence of highly
conventionalized combinations of words and general world knowledge, may
come into play and oyerride the semantic mismatch described above. For example, John walked hk dog and Fido was walked by lohn tonight sound highly
natural.
Let us now look at sentences with reduced relatives headed by passive
participles derived from unaccusativeverbs. In (l7a) the subject ofthe un-
$
accusativemelted, the butter, corresponds to the object of the active transitive
melted in ( l7b), they are both entailed to have at leasttwo Proto-patient prop-
7,
FfarraFilip et al
'(lrrlrl',c
'Incremental
of slale' and
Theme'.Hence,they are "very good"
cl tics:
[)at ic rrts,arr<I rvr'(.;rl I expect that both the transitive and passivelusesof n'telted
i l l r ' P c 'l1r ' .1. 1 r; 't rr r ' P I a l 1 l e .
(.17) :r. 'l hc lruttgl Mlltl'ED in the pan.
'l'lrc
r r'ol<IUEUI'EDthe butterin the pan.
b.
( l8)
a. .l'lrcllqltg1MELI'EDin the pan wasfresh.
b. # !'!Lebu{ql MEUIED on the stovedripped onto the kitchen floor.
As is prcclictcrll,y the hypothesisin (13), (18a) is judged easierto processthan
(l8b). (lSb) corrtainsthe matrix verb drippedthat entailsthat the referentof
its subjectargunrentntovesrelativeto the position of another participant,and
berrcecan be vioved as entailing one Proto-Agent property in its subject argunrcnt.This, lrolvcvcr,is inconsistentwith the requirementstatedin our hypothesis(13) that tlrc subjectNP in the matrix clausematchesin its Proto-Patient
properties the lhernatic rnake up of the PRO-subject of the reduced relative
clarrse.(l [ta) contains tlre stativepredicate befresh in the matrix clause,which
entrrilsrro Prolo-Agentpropertiesin its subjectargument, and hence(18a) is
n l ( ) r ea c c e l ) t u l rtl h
calr( I8b).
4.1 An tll'S(; it1'proaclr
Irr the pasl tcn ycars or so tlrere has been a growing convergenceof results and
rrrclhoclokrgicalirssrrnrptionscoming from psycholinguistics and theoretical
irr llrl rlornain <lf constraint-basedapproachesto natural language
lirrrlrristics
tk'sr.ription(r'.ri.,l\rllarcl and Sag, 1987;Pollard and Sag,1994;Sag,1998,for
forareview
e r ' r r r r p f e ; s e ea 'rlr c n h i r r r s a n d l i u e s w eIl9l ,9 5 a n d M a c D o n a l d , 1 9 9 7
approacl.res
in psycholinguistics).
Theysharetwo main asol'r orrstlairrl"lr;rscd
interpretation requiressatisfactionof multiple
srrrrrptions:l;irsl, a serrtence's
(1'r'ssilrly,lif1i'rerrt ialll' weighted)constraintsfrom various domains of linguisli< ;rnclnorr lirrlirristicknowledge.Second,the integrationof such diverseconstrlints is lacilitatedby the information containedin lexicalentries.Verb-based
syrrtacticarrd sernanticpatternsprovide a guide for interpretingkey aspectsof
sl nrcture and rneaning,whereby semantic constraints often have
tlrc senterrce's
a l ' r i v i l e g c tsl t a l l r s .
'I'hc
lcxicalcorrstrairrt-based
approachproposedherehas all the main hallrr:rrks of recerrtvcrsions of HPSG (see Sag, 1998, for example). Assumptiorrs aborrt lexit:alsernanticsof verbs and linguistic information directly associatedwitlr cxtla-lirrguistic context and generalworld knowledge are influ-
Reducedrelativesjudged hard require constraint_based
analyses
enced by Fillmore's work and construction Grammar (seeFillmore
and Kay, in
press).The grammar assumedhere is monostratal, non-derivational
and nonmodular. It is characterized declaratively by specifying types
of well_formed
linguistic expressions(e.g., words, phrases,part of speech
classes,argumenr
structure classes,and traditional morphological classes,for
example) and con_
straints on those types. Alr properties oflinguistic expressions
are represented
as feature structures- Language-particurar rules and universal
principres are
characterized as systems of constraints on feature structures.
The main explanatory mechanism is unification in the narrow sense
of structure sharing
oftoken-identical feature structures (cf. pollard and sag, 1994).
Since lexical entries constitute the key ingredient for interpreting
the main
aspectsof the sentencet structure and meaning, and facilitate
integra-tionof diversetypesof knowledge,let us introduce their main features
using a simplified
lexical entryfor the transitive activeracedin (19):
( ie)
.l
-itll
(19) contains phonological,syntactic,semantic and pragmatic
information,
encoded as valuesof the feature attributes pHoN, syN, sEM
and CONTEXT,
respectively.The value of SyN encodessyntactic information required
for con_
structing syntactic projections headed by raced.The linking
bei*e.n the syntactic (SYN) and semantic (sEM) structure in the lexicon is
mediated via coindexation of syntacticarguments and thematic argument slots,
and motivated
by Dowty's Argument selection principle (here given in (12)).
Each argurnenr
slot in the thematic structure of a verb correspondsto a cluster proto-Age't
of
and/or Proto-Patient properties (cf. Dowty, 1991).Thematic argument
slots in
turn are co-indexedwith individuars in the predication feature
structure PRED,
which together with 'psoa' (param etrized state of affairs) constitutes
the value
of GoNTENT. The feature structure pRED capturesthe assumption
that verbs
semantically expressrelations between individuals. The attributes .racer,
and
'racee',
which correspond to'frame-specific participants'in Fillmore (19g6)
or
'individual
thematic roles' in Dowty (19g9), include properties that we
asso_
ciate with the individuals 'i' and'j' on the basisof knowing that
the statement
27,
Reducedrelativesjudged hard require constraint-basedanalyses 275
4 I l a r r aF i l i pc t a l .
'i
r:r,r:<lj' is Il.rre.Irr a given single-clausepredication, further semantic restrictiorrson particilxrrrtsare imposed by the interpretationof noun phrases'For
exrrrrirlg,'lr.r.,'r'il' rvill be constrainedby the content of the NP filling the
'IllNP'pl:r<'c. l'lllil)
does not provide an exhaustiveaccount of all that we
l<rrolvalrotrt llre rrreattittgof a given verb. What role an individual plays in a
g,ivcnsituirtiotr rlelrettdson a number of other factors,includingworld knowledge,which is errc,rtleclunder'psoa'.(For a related,though not identical' use of
'psrra'
5.. f \ rllald an<lSag,I994; Sagand Wasow, 1997.)I'extcalentries of verbs
itrfcrrmationabout the occurrenceof a given verb form
also inclrrrle[r'cqtrr,'ncy
;rlrotttits arguntentstructures,and the like.
in tlre langrrage,
Apart liorrr tlre lexicon, the grammar will minimally include the level of
verb forurs arrrl tlre syntactic level with phrasal templates.This is illustrated in
a h i g h l ys i r r r p l i l i e tI l; i g u r e2 .
VFoRMS
,aced
tacecl
passive participle
raced
pas! active participle
LEXICON
PHRASAL
TEMPI"ATES
model.
outlitreof a constraint-based
Figrrre2. A sirnplilietl
tylres each level of representationare cross-classifiedin multiple
In g,cr-reral,
"l
inhcritancehierarchiesaccordingto their sharedinformation. (Due to the limitation of space,this is not representedin Figure 2.) The information shared
by a given class0f'objects is associatedwith a general type and is automatically passeddorvn frotn the general type to specific members of the class.For
exar)rple,I{n(ll.,l)Z antl IIACEDS inherit infonnation from the generic lexical cntry ftrr trnlr.sitiveverbs, here representedby the node Vt. Types direcdy
sul)sunted urrtler the salne supertype represent mutually inhibitory alternativcs, which ofterr representmultiple interpretation alternatives and differ in
frcrltrencyof occurrettceitr the language.For example, RACED2 (active past
terrse) an<lI{ACIil)3 (passiveparticiple) are mutually exclusive,here indicated
by the thick slartctl line lretweenRACED2 and RACED3.The activeintransilivr,'rrse<tI'roccrlis ntclte ft'equentthan the activetransitive one. We assumethat
srrrlrllctlrrcnt.yirrftrrrttaliouis encodedin the lexicalentriesof verbs.
Unification allows us to represent dependenciesand connections within
one particular level of representation and also among different levels. Feature structures representing compatible types are unified in a new coherent structure by linking them to a single feature structure, which is shown
with straight lines (not all such possible connections are here indicated): e.g.,
IVFORM PAST.ACTIVEI U [SYN Vi]. Featurestructures representingincompatible types cannot be unified: for example, active verbs cannot be projected
into a passiveclause. One advantage of this system is that it allows us to capture
the observation that different types of information that characterizethe use of
a given word are dependent on each other so that accessingone type ofinformation during sentenceprocessingresultsin accessingothers compatible with
it. For example, if the sequenceThe horseraced... is understood as the main
clause, the information associatedwith the verb racedwilTbe a complex feature
structure comprising the information that this verb shareswith all active past
tense verbs. If the same sequenceis understood as the head noun modified by
a reduced relative clause, racedwilT be associatedwith the information shared
with all passiveparticiples, and due to its passiveargument structure it will also
activatethe information associatedwith the active transitive useof race.
S. Empirical study of effects at the main verb
We conducted a rating study in which we had six subjectscomplete questionnairesin which they made judgments about four of the dimensions that Dowty
identified as being part of the Proto-Agent cluster: 'volition', 'sentience','causing an event or changeof state',and'movement'.s The questions concernedthe
subject argument of the main verb in the matrix clause.Thus to obtain ratings
for The horse raced past the barn died, the subject would rate The horse died.
Each simple sentencein the latter set of data was associatedwith four questions
designedto illicit judgments about the four main Proto-Agent properties entailed by the verb for its subject argument. Each question was answeredby our
subjects using a scale from I to 5. For example, in the caseof 'volition', I would
indicate a completely non-volitional participation of the individual denoted by
the subject argument (e.g.,The horsedied) and 5 would a fully volitional participation (e.g.,Thepatients complained).Wethen averagedtheseratings to come
up with a composite Proto-Agent rating, with 1.0 being the lowest and 5.0,
the highest. Subsequently,we selectedmatched pairs of reduced relativeswith
different main verbs, e.g., The victims rushed to the hospital complained/died,
in which participants assigneddifferent Proto-Agent ratings for the two main
Reducedrelativesjudged hard require constraint-basedanalyses
,.76 I [ ; r r r ' lr i l i l ' , ' t : r l .
'l'lrcyiclifits
We were ableto idendied vs.The victimsconxplained'
vcrl)s(c.tI.,
We then had
tify 2l rrr;rltlretlpairs of reclucedrelativesthat met this criterion.
verbs, e'g',
main
these
,tnotlrcr g,t.t,rrpof subjectsrate reduced relativesusing
'I']rc
vit I i'rrs,r,rl,r',1la tlrc lnspital complained/dietlshortly after arrival'
'lhblc 3. llarc,l difficultyfor reducedrelativeswith main verbsdifferingin the ProtorePresent
to their subjectargument.Numbersin parentheses
assigned
AgentPrOperti,:s
Merlo'sclaimsthough, this resultis completelyconsistentwith currant constraint-based
lexicalistmodels.We alsopresentedan analysisof the unergative/unaccusative
distinctionusingthematicrole propertiesalongwith some
preliminarysupportingevidence.In future researchit will be important to
combinemore sophisticated
thematicrole representations
into a constraintmodel.
basedprocessing
l h e r r t c a t tI ' t o l o - A g c l t l r a t i n g
Acknowledgments
passiveprrticiple derivedfrom
u n a c c u s a t i v ev e r b s
u l r e r g a t i v ev e r l ) s
2.32
2.81
(t.37)
(2.04)
2.50
3.3r
(2.35)
(3.83)
'l'he
the mean
tlata are presentedin Table 3. The numbers in brackets indicate
argument,
ratings ftrr verbs with low Proto-Agent entailments in their subject
in their sub.nd th. meirn ratings for verbswith high Proto-Agent entailments
a main
revealed
ratings
Arr ANOVA conducted on the difficulty
icct rrrg-trntt'ttt.
of
,'ffe,t of vetl',.:lass,F(l'zO)=g'so, p<'01,a main effectof the Proto-Agency
Overt l r c r r r : r i rvr r : r l r ,l r ( 1 , 2 0=) 5 . 0 2 ,p < . 0 5 a n d n o i n t e r a c t i o n ,F ( 1 , 2 0 ) = l ' 1 0 '
properties
Proto-Agent
higher
,rll,tlrcrr,r ctlrrceclrelativeswith main verbswith
properties'
\vcl('ilrr(r (' rliflictrlt than reclucedrelativeswith lower Proto-Agent
'l'rr
this section, we showed that the unaccusative-unergative
srrrrrrrrariz-e
r l i s t i r r t : t i otrlrr a t s t e v e n s o n a n d M e r l o c h a r a c t e r i z e a s a s y n t a c t i c d i s t i n c t i o n c o r clausescan be
r.clal.tl rvitlr tlil'liculty ot easeof processingin reduced relative
roles' One adI.c-c;tstas a tlistinclioD that concernsthe assignmentof thematic
is that
phenomenon
vaullrgc of tlris llovel way of looking at the garden-path
comit all.lvs us t. turrlerstandsomething that has never been systematically
a
sentence
in
predicate
main
the
rrrcutetl,rrr |cftlre: nanely, the influence of
of the garden-patheffect.The analysisin terms of Dowty's
()n tlte rrragrritu<le
predictions here.
therrraticr.oles,lbrrnulated in (13), also makes the correct
(1988),
,l'hcse
Thnenhaus
and
carlson
resrrltsalsg sqpport the claim made by
Thnenhaus
,lhrrcnlraus
by
ancl(larlson ( 1989),and in a number of later studies
in languagecomancl his collirlxrrators,that thematic roles play a central role
with an
is
consistent
analysis
prc|c,si.1. We also showed that our thematic
t l y nlotivatedlil guisticmodel'
i ncleperttlcn
,lhkerr tt,eether, tlte current work confirms stevenson and Merlo's finddeing thirt scnlel)ceswith reduced relativesheaded by passiveparticiples
sentences
liie,l {l ,,rrr rtrtergativeverbs pose more processing difficulty than
verbs.Contrary to Stevensonand
relativeslrasedon unaccusative
rvillr rr.,lrr,..,',1
The researchpresentedin this paperwassupportedNIH grant HD 27206ancj
by NSFgrantSBR-9511340.
Many thanksto MichaelSpiveyfor his comments
on a previousdraft of this paper and to SarahScheidelfor her help with the
questionnaires.
gratefulto PaolaMerlo and SuzanneStevenWe areespecially
sonfor helpfuldiscussions
and for providinguswith the corpuscountswe used
in our model.
Notes
r.
'+'
'*'
Departmentof Linguistics, Department of Brain and CognitiveSciences.
z. The unaccusative/unergative
distinction (e.g.,melt vs.mce)wasintroducedby Perlmutter
( 1978),and alsonoticed by (Halt, 1965).
3. According to semanticcharacterizationsgiven by Var.rValin (1990) and Dowry (1991),
for example,unergativeverbs tend to entail agentivity in their single argument and to be
aspectuallyatelic. Unaccusativeverbs take a patient-like argument and are mostly telic.
4. It might be objected that our examples in (3) are easyto process,becausethey involve
complex unaccusativepredicates,rather than unergativeverbs.However, for English at least,
there seemto be no convincinggrammaticaltestsfor the unaccusativestatusof the com'unergativeverb +
bination
directional PP'.(SeeLevin and Rappapport-Hovav,1995:t88
and elsewhere,for a discussionofpossible candidatetests,such as the occurrenceofunaccusativesin the causativealternation.)
'referent
exists inde5. Onc of Dowty's Proto-Agent properties was not included: namely,
pendent of action ofverb'. It doesnot matter for our analysis,given that the constructions
under considerationhavethe samevaluefor this feature.
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