a corpus-based approach to argument structure goals functional

7/29/2019 A Corpus-based Approach to Argument Structure Goals Functional

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A corpus-based approach to argumentstructure

Jos M. Garca-Miguel

Universidade de [email protected]

2007 RRG International Conference (Mxico) RRG 2007Garca-Miguel: Corpus-based approach to argument structure

Goals

To present some possibilities offered by asyntacto-semantic database (ADESSE) for thestudy of the interactions of verbs and constructionin Spanish

To introduce the main criteria used in the buildingof such a database

To overview some general features of argument

structure in Spanish

To compare both the approach and the results ofADESSE with some insightful proposals of RRGtheory

RRG 2007Garca-Miguel: Corpus-based approach to argument structure 3

Functional Grammar(s)

This talk is not specifically about RRG, but it takes asbackground many ideas shared by most functionalists

Functionalist share the idea that grammar associates formswith meanings and discourse functions: language is a system of communicative social action in which

grammatical structures are employed to express meaning incontext (Van Valin 2005: 1)

They differ with respect to (among other things): Standards of adequacy (typological, psychological, ) How the conceive the relation system - use The role of formalization and the specifics of the formalism

Moderate functionalists (RRG) Extreme functionalists

RRG 2007Garca-Miguel: Corpus-based approach to argument structure

LEXICON

CONSTRUCTIONAL

SCHEMAS

LANGUAGE

USE

'entrenchment'

(frequency memory)

(A simplified model of)Functional grammar


Variation and Grammar:

the 'emergentist' view

"Grammar is built up from specific instancesof use which marry lexical items withconstructions; it is routinized and entrenchedby repetition and schematized by thecategorization of exemplars" (Bybee 2006)

Grammar is not fixed and absolute with aittle variation sprinkled on the top, but it isvariable and probabilistic to its very core"(Bybee & Hopper 2001)


Corpus linguistics

Nowadays, to study language use and frequencyof words and constructions means corpuslinguistics

Computers have made possible the quick search oflarge bodies of real text and make easier the task ofanalysing, annotating and storing linguistic data

Some linguists (e.g. Butler think that functional linguistics should not only corpus-based but corpus-driven


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Corpus linguistics

me problems:

The words and patterns that we find in the corpus should not beconfused with the words and patterns that are possible in thelanguage

A corpus cannot tell us what is not possible

Every (fragment in the) corpus needs some analysis andinterpretation by the linguist

"The conclusion is that 'intuition-based' linguists and

corpus-based' linguists need each other. Or better, that thetwo kinds of linguists, wherever possible, should exist in thesame body" (Fillmore 1992: 35)


Corpus linguistics and syntax

"Corpus linguistic research has been largely limited to phenomenathat can be accessed via searches on particular words ()

However, a (theoretical) syntactician is usually interested in moreabstract structural properties that cannot be investigated easily inthis way"(Manning 2003: 294)

I.e., it is not always enough with google search of raw text, nor even withmorphosyntactically annotated corpora (or with texts accompanied ofinterlinearized glosses)

We need detailed syntactic and semantic annotation ofcorpora


ADESSE

ESSE =Base de datos de verbos, Alternancias de Ditesis yEsquemas Sintactico-Semnticos del EspaolSyntactic Database of Verbs, Diathesis Alternations and

Constructional Schemas of Spanish]

http://adesse.uvigo.es/

An on-going project funded by Spanish MEC and EU funds

Goal

A database with syntactic and semanticnformation for all the verbs and clauses in acorpus of Spanish


BDSBase de Datos Sintcticos del espaol actualhttp://www.bds.usc.es/

A database with the (manual) syntactic analysis of 159,00clauses of the corpus ARThus

ARTHUS Corpus (Archivo de Textos Hispnicos de la Universidade Santiago de Compostela)

1.5 million words

Textual genres: narrative (37%), spoken (19%), essay (17%),theater (15%), journalistic (12%)

Origin: Spain (79%), Americas (21%)

ADESSE antecedent


BDS ADESSEUSC 1990-1999]

Syntacticinformation

Grammatical featuresof clauses, verbs andarguments of thecorpus[Each record (clause):64 fields]

[Univ. of Vigo 2002- ]

All the syntactic information fromBDS

+Semantic information

- Verb senses

- Verb classes

- Semantic roles

159.000 clauses

3.500 verbs

13.500 valency patterns



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(part of) a record in ADESSE

IVDder

S D Int Schema

novioautomvil

ReceiverPossessionDonorm RoleNPNPnt Category

le3plreement

IObjDObjSubjnt Function

A2A1A0

Activeice

Transfer of possessionrb class

REGALARED

Al novio le regalaron un automvil convertible [CRO: 44, 1]'They gave the bridegroom a convertible car as gift'

XT

Valueeld


BDS/ADESSE

Other grammatical features

Clause: Clause Type (main, subordinate, ) Mood Tense Modal and Phase Auxiliaries Negation Illocutionary force Voice

Arguments: Definiteness Number Person

SENTENCE

CLAUSE

CORE

NUC

PRED

DP

NPNP

AGR AGR

novio le regalaron un automvil

a: DAT ACTIVE PSA:NOM (ACC)

3pl], )] CAUSE [BECOME have (novio, automvil)]

0:donor>

Cat: < NP , NP>

SchemaSynt Funct: < S D I>

Order: < I V S >

Agr: < le, S3pl >

Sem roles

UNDERGOERACTORNMR

RRG representation and ADESSE features


BDS/ADESSE database aims to be theory-neutral

it only assumes common Basic Linguistic Theory(in the sense proposed by Dixon)

but is fairly compatible with functional andconstructional grammars

the approach is aimed to correct or complementbasic linguistic theory (or theories) in the light ofcorpus evidence


Basic strategies:

Verbs and arguments in ADESSEBDS provides a syntactic characterization ofarguments and constructions ESCRIBIR 'write'

Subj DO IO Subj DO

SUSTITUIR 'substitute, replace' Subj DO porNP Subj DO

ENSEAR

Subj DO IO Subj DO a Inf


Verbs and arguments in ADESSEIn many cases, each syntactic construction selections asubset of the potential participants of the scene evoked bythe verb

a) Juan [0] le escribi una carta [1] a su madre [2] sobre susrecuerdos de infancia [3]John wrote a letter to his mother about his childhoodremembrances

b) Juan [0] escribi una carta [1]John wrote a letter

c) Juan [0] le escribi a su madre [2]John wrote to his mother

The task in ADESSE is to annotate which of the potentiparticipants is selected in each syntactic schema


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Verbs and arguments in ADESSE

e same syntactic construction can be mapped with differentconfigurations of semantic arguments

Sustituir'replace'a) Deco [1] sustituy a Xavi[2]

Deco replaced Xavi

b) Rijkaard[0] sustituy a Xavi[2]Rijkaard replaced Xavi

c) Rijkaard[0] sustituy a Xavi[2]por Deco [1]Rijkaard replaced Xavi with Deco

e same set of semantic arguments can be linked to different

syntactic patterns Ensear'teach'

a) Ella [0] le [1] enseaba su idioma [2]She taught him her language

b) Ella [0] ense al nio [1] a caminar[2]She taught the baby how to walk


Verbs and Arguments in ADESSE

Valency potential of a lexical entry: which arguments can be selected by a given verb?

Valency realizations (diatheses): which arguments are actually expressed

which is syntactic realization of each argument

voice

(The strategy in ADESSE is to define the valency potential of each verbentry and to register in the corpus all the valency realizations)

RRG 2007Garca-Miguel: Corpus-based approach to argument structure 21 RRG 2007Garca-Miguel: Corpus-based approach to argument structure 2

Valency patterns and frequency

Enseaban a saber comer[MAD:277]2A2:Obl(a)A0:Subj

Enseaban cosas tiles [MAD:277]18A2:DObjA0:Subj

A coser la enseaban desde pequea [USOS:71A2:Obl(a)A1:DObjA0:Subj

Kant ense en Knigsberg[TIE:195]4A0:Subj

Eso me ensear a fiarme de ti [PAI:161]22A2:Obl(a)A1:IObjA0:Subj

Si su hijo no sabe, l le ensear [SON:99]28A1:IObjA0:Subj

Me enseaba su idioma [JOV:134]58A2:DObjA1:IObjA0:Subj

ExamplesNValency pattterns in Active Voice

A2

(Content)A1

(Learner)A0

(Teacher)

Valency potential of the verb ENSEAR 'teach'


Arguments and gradienceValency patterns occur in the corpus with differentfrequency, ranging from the more usual to the rare andunexpected.

As a consequence, verb arguments are not alwayssyntactically realized Obligatoriness optionality of arguments is not a yes or no matter,

but a gradient

Obligatory arguments are those (referential) elements morefrequently tied to the verb in texts

Because obligatoriness is one of the main criteria for theargument adjunct distinction, this is also a gradient


Arguments and gradienceArguments ofEnsear'teach' (N clauses =139)

(75.5 %)105Content2

(79.9 %)111Learner1

(99.3 %)138Teacher0

Arguments ofEscribir'write' (N clauses = 321)

(3.1 %)10Topic4(26.5 %)85Receiver2

(64.8 %)208Text1

(93.5 %)300Writer0


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Frequency and argument structure

Argument structure' needs to be replaced by agreatly enriched probabilistic theory capturing theentire range of combinations of predicates andparticipants that people have stored as sorted andorganized memories of what they have heard andrepeated over a lifetime of language use

(Thompson & Hopper 2001: 47)



Manning (2003)

Many subcategorization distinctions presented in thelinguistics literature as categorical are actuallycounterexemplified in studies of large corpora of writtenlanguage use.

We can get a much better picture of what is going on byestimating a probability mass function (pmf) over thesubcategorization patterns for the verbs in question.

we can put a probability function over the kinds ofdependents to expect with a verb or class, conditioned onvarious features. (302)



Proposals

The meaning of a verb determines its contexts of use ands determined by its contexts of use

Argument structure is a generalization over registered use,where frequency/probability of cooccurrence is a speciallymportant factor in the entrenchment of a valency pattern.

nstead of obligatory arguments, or participants inherent toa scene, our past linguistic experiences provides us with

certain probability expectations about the reference to acertain participant type in the scenes evoked by a verb


Verbs and constructions

A Basic problem: Polisemy and contextualacommodation. Changes in meaning when a verbenters alternating valency patterns

The formalization of syntactic alternations different lexical entries: each different meaning is a

different verb entry

lexical rules (RRG), relating different LS

underspecification: only one verb meaning, thedifferences in meaning should be attributed to theconstructions


Verbs and constructionsStrategies in ADESSElexical rules or constructions?

Underspecification: Reduce lexical entries to aminimum (searching wider coverage of the corpus andless task consuming)

(new strategy in ADESSE-II): Levels of granularity in thedefinition of verb senses

Nevertheless, this is a 'false dichotomy' (Croft 2003), motivated either

by the level of granularity or by the perspective adopted when linkingsyntax and semantics (Van Valin 2004)


Lexical entries in ADESSETwo levels: Level 1: Macro-aception [verb 'meaning'], associated with a semantic

domain and a set of participant roles Level 2: (Sub)aception [verb 'senses'] {work in progress}

Volver1.2 (met) 'return to a state or activity'

Volver-3 '(cause) become'

Volver-2 'turn round'

Volver1.1 (lit) 'return to a place'Volver-1 'return, go back'

Ensear-2 'teach'

Ensear-1 'show'

Conocer 1.3 'understand, know deeply'

Conocer 1.2 'recognize, distinguish'

Conocer 1.1 'get to know'Conocer-1 'know'

LEVEL 2LEVEL 1


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Verb Entries

(At level 1) We distinguish verb entries when they areassociated with different sets of semantic roles that means differences in valency potential,

not in valency realization

We try to limit sense distinctions to a minimum, but we mustdistinguish senses that cannot be 'unified': partir 1 (go away) vs.partir 2(break) saber 1 (know) vs. saber 2(taste)

or (less clearly) senses which are related with different lexical

classes ensear 1 ('show') vs ensear 2('teach')

Anyway, there no clear boundaries between senses at anylevel (cf. Kilgarriff 1997)


Unifying verb senses

Typically included in one single verb entry (level 1):

Diathesis alternations(causative / inchoative, locative alternation, ...)

Semantic differences are attributed primarily to the construction, nto the verb

Paradigmatic alternatives within an argument(For ex: write a letter / a novel / a musical work)

Meaning accommodation or co-compositionality, but not differentverb senses

Metaphoric and other figurative uses they are annotated as the literal uses, but marked as figurative


Paths of Schematization

IODOPredSubjENSEAR

ingls y francsenseabaMi padre

(to somebody)(a language)teaches(somebody)

OIndODirensearSuj

My father taught us English and French

[[SEVSEV: 277]: 277]

ching verbs/frame

nos


Syntactic Patterns Verbs

Once we have defined verb entries and syntactic patterns, we cantake two complementary (not necessarily incompatible) points ofview concerning the association of verbs and constructions:

P. of v. of the verb:alternations (for ex., Levin 1993) of valency patternskeeping, as far as possible, the lexical elements Me ense a cantar "She taught me to sing"

Me ense canto "She taught me singing"

P. de v. of the construction:'surface generalizations' concerning uses of a

constructional schema with different lexical elements(Goldberg 1995, 2000; also Dowty 1998)

Me ense a cantar "She taught me to sing"

Me oblig a cantar "She forced me to sing"


Verbs and alternationsany lexicalist approaches havecused on whether verbs admitscertain alternation, for ex. the

ausative alternation

r, alternatively, whether theyan be combined with a certainpe of argument) No

Yes

A0 A1

YesCrecer

'grow'

YesCambiar'change'

A1

YesYesEnsear'teach'

YesNoAprender'learn'

N1 N2A0 N1 N2

this is not a yes/no question,ough the syntagmatic axis

serve to describe theavioral profile of verbs


Arguments and behaviour profile:

Change of state verbs

ABRIR

CAMBIAR

CERR

AR

ROMPE

R

E

NCEN

DER

CREC

ER

AR

REG

LAR

APAG

AR

LIMPIAR

ORGANIZAR

RESO

LVER

AUME

NTAR

BOR

RAR

PROLON

GAR

ILUMI

NAR

0: AGT

1: PAT

88%100%

90%85%83%

100%100%99%94%99%100%100%100%100%98%

81%

38%

90%

81%

100%

0%

88%

75%

100%

88% 90%

45%

83%

54%

72%

0%10%20%

30%40%

50%

60%

70%

80%

90%

100%


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Arguments and behavior profile:Verbs of knowledge

SABE

R

CONO

CER

RECORD

AR

COMPR

ENDER

ESTU

DIAR

OLVIDAR

ACORDA

R

APREN

DER

ENTE

RAR

IMAGIN

AR

ENSEAR

SOA

R

DEMOSTRA

R

0: Inducer

2: Content

1: Cognizer

0%

20%

40%

60%

80%

100%


Valency alternations and behavior profil

Each lexical element can be described in terms of thefeatures and contructions it combines with in context (itsyntagmatic profile)

A relevant part of the profile of a verb are its constructionaschemas, the realizations of its arguments, and thefrequencies of schemas and argument realizations

Two verbs of the same class may have similar sintagmaticcombination and differ in the relative frequency of each

combination, and as a consequence in the relativefrequency of their core arguments

It is hypothesized that the differences in frequency aremotivated by differences in meaning


"Surface generalizations"

(cf. Goldberg 1995, 2002; also Dowty 2000)

e can see the relation between verbs and constructionsfrom the point of view of the constructions.

That is, any constructional schema (vgr., passive, doubleobject, ) can be described by itself and not as derivedfrom any other alternating schema.

The meaning of a constructional schema is established(and learned) by generalizing from the meaning ofparticular utterances that instantiate the schema An essential part of the characterization of a constructional schema

comes from its association with a class of verbs. The strength of the association of a constructional schema and a

verb should be measured on the basis of a (syntactically annotated)corpus


Verbs in the schema

El profesor le dejaba la casa para que la habitara [HI96'Lend'DEJAR

Le trae un kilo de bombones a mam [BAI:424]96'Bring'TRAER

Si se te cae un ojo, te pondrn otro enseguida [MOR:101'Put'PONER

Le explic cmo funcionaba la imprenta [TER: 062]112'Explain'EXPLICAR

No puedo ofrecerles grandes comodidades [LAB: 115119'Offer'OFRECER

Me permite usar su telfono? [SON: 285]124'Allow'PERMITIR

Me pregunt que si tena dinero [LAB: 268]219'Ask, inquire'PREGUNTAR

Nos pidi que lo esperramos [HIS: 013]273'Ask, request'PEDIR

Rosetta le contaba que el otro iba empeorando [SON:308'Tell'CONTAR

Le hizo la promesa de llevarle al local[TER: 119]514'Make'HACER

Le dije que no quera volver[TER: 046]599'Say, tell'DECIR

Mi padre slo me da dinero para estudiar[SON:115]1272'Give'DAR

ExampleNMeaningVERB


Verb classes of clauses in the schema

Active

6158127(causarcause)20118EXISTENTIAL

costarcost17180ATTRIBUTIVE

tocartouch80305OTHER FACTS

abriropen140430CHANGES

recordarremember64615MENTAL

traerbring88686LOC & MOVEMENT

hacerdo, make18806MODULATION

decirsay, tell1082419COMMUNICATION

dargive802568POSSESSION

Example verbsVerbsClausesCLASS


S D/Ian a Inf

More frequent verbs in the constructional schema S D/Ian a Inf (ADESSE):

Me mand a comprar pan9DesplazamientoMANDAR

Me forz a abandonar el intento9ObligacinFORZAR

Me sac a bailar//lo sac a saludar10DesplazamientoSACAR

Me anim a escribir10InduccinANIMAR

(esto) Me impuls a escribir11InduccinIMPULSAR

Me ense a coser23ConocimientoENSEAR

Me invit a ver su casa42InduccinINVITAR

Me llev a ver una casa52DesplazamientoLLEVAR

Me ayud a triunfar70InduccinAYUDAR

Me oblig a salir94ObligacinOBLIGAR

ExampleNClassVERB


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Paths of Schematization

Grouping verbs in classeso main paths of schematization / generalization:A verb is related, by its lexical meaning, with other partly similar verbs ensear-1 'show' mostrar'show', ver'see', mirar'look'

ensear-2'teach' aprender 'learn', estudiar'study', saber'know'

On the other hand, by being used in a syntactic schema, it issemantically construed as other verbs that realize the same pattern ensear dar'give', decir `say', contar 'tell', preguntar'ask',

ensear dar'give', decir `say', contar 'tell', preguntar,

That puts each verb in a complex network of semantic relations


S D I S D/I a infinitive

darhacer decir

ENSEAR

invitarayudar obligar

ver

mostrar

mirar

aprendersaber

conocer estudiar


Semantic Classes of Verbs/Preds

wo main criteria of semantic classification of verbs(both of them used in RRG)

Aktionsart classes (based on LS) State, Activity, Achievement, Accomplishment, etc

Ontological/conceptual classes(based on the 'constant' part of LS) Location, perception, cognition, consumption, etc.


ADESSE Verb Classes

Goal of ADESSE verb classification:to represent generalizations over types of conceptualframes evoked by individual verbs

It is a conceptual/ontological classification, inspired inlexical relations of synonymy and hyponymy/troponymy,not aspectual nor primarily syntactic

It is a hierarchical classification, with up to four levels at thpresent stage Top level classes 6 options

[~Hallidays 'process types'] Classes recognized so far 60 options

With the possibility of increase granularity in the future


ADESSE hierarchy of semantic classes

tocar33 Other facts

tratar, atreverse61 Dispositivehacer, obligar60 CausativeMODULATION

ser21 Attributive

pedir42 Command

estar, poner312 Location

creer132 Belief

haber, aparecer

criticardecir, hablar

destruirromper, cambiarhacer, crear

ir, llevartener, dar

saber, ensearver, escuchar

gustar, temerExamples

41 Judgement

XISTENTIAL

OMMUNICATION

323 Destruction

322 Modification

321 Creation32 Change

311 Displacement31 "Space"MATERIAL

22 Possession

ELATIONAL

131 Knowledge13 Cognition

12 Perception

11 FeelingMENTAL


ADESSE top-level classes

Hacermake

HaberexistDecirsay

RerlaughTocar 'touch'

Abriropen

Irgo

TenerhaveSerbe

SaberknowVerseeGustarlike

Exs

1583113

1171552399

109276413141761544131472

CLAUSE

3978TOTAL1396 MODULATION

2015 EXISTENTIAL3354 COMMUNICATION33134 Behaviour42933 Other facts92332 Change62931 "Space"3 MATERIAL18522 Possession23221 Attributive2 RELATIONAL17113 Cognition11512 Perception27111 Feeling1 MENTAL

VERBS


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Semantic roles and verb classes

Each (sub)class is associated with a set of semantic rolesprototypical for the cognitive domain evoked

Source

--

Agent

Initiator (causer)

Initiator (causer)

Initial-possessor(Donor)

Initiator (causer)

Initiator (causer)

0

ReceiverMessageSayermunication

Patientge

LocativeThemeization

GoalThemeacement

PossessedFinal possessor(Receiver)

sfer

PossessedPossessoression

ContentCognizerition

PerceivedPerceivereption

StimulusSenserng

--21Class


Semantic roles

There is no single list of semantic roles, and role definitionis made at three levels:

Verb-specific roles(representing valency potential) EscribirA0:Writer, A1:Text, A2:Receiver, A3:Topic EnsearA0: Teacher, A1: Learner; A2: Content

Class-specific roles Communication Sayer, Message, Receiver, Topic

Cognition Cognizer, Content

SynSem Schemas (valency realizations), pointing toverb-specific roles Active Suj=A0 DObj=A1 IObj=A2

Le escriba canciones de amor


Semantic roles, verbs and semantic classes

Each verb entry is associated with a set of argumentsembracing any possible core participant with this verb

By default, verb arguments inherit the role labels from theclass(es) to which the verb belongs

A2TextWriter

A3A1A0cribir write

MMUNICATION Sayer Message Receiver Topic

utut,, sometimessometimes,, verbverb--specificspecific rolerole labelslabels areare alsoalso usedused

EATION Creator Effected


RRG: Generalized Semantic Roles


ADESSE roles

destruir.01Destroyed

romper.01, cambiar.01Affected

hacer.01, crear.01Created

Patient

tener.01, dar.01Possessor

saber.01, ensear.01, creer.01Cognizer

ver.01, mirar.01Perceiver

gustar.01, temer.01Emoter

Experiencer

saber.02, ensear.02, creer.02Content

ver.02, mirar.02Perceived

gustar.02, temer.02Emoted

Stimulus

tener.02, dar.02Possessed

CLASS-SPECIFIC ROLES VERB-SPECIFIC ROLES

ncreasing generalization


Generalized Semantic Roles

(still a tentative in ADESSE)Common LS templates of lexical entries

pred'(x) | BECOME pred'(x) pred'(x, y) | BECOME pred' (x, y) [do' (z)] CAUSE [BECOME pred'(x, (y))]

Default indices for arguments

z = A0 (initiator or causer) x = A1 (first argument ofpred') y = A2 (second argument ofpred')

that is only the default numbering, because many verbs have a more complexsemantic structure


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Generalized Semantic Roles

z = A0 (initiator or causer)

x = A1 (first argument ofpred')

y = A2 (second argument ofpred')

A0, A1, and A2 are the closest Adesse's relatives ofmacro-roles Actor and Undergoer


Generalized Semantic Roles:A0 A1 A2 vs Actor Undergoer

The ADESSE hierarchy A0 A1 A2 is similar to the Actor-undergoer hierarchy:

ACTOR UNDERGOER

Arg of

DO

1st

arg. of

do(x,

1st

arg. of

pred (x,y)

2nd

arg of

pred (x,y)

Arg of

pred(x)

A0 A1 A2

Arg of[do(x,)] CAUSE 1

st

arg. ofdo(x, 1

st

arg. ofpred (x,y)orpred(x)

2

nd

arg ofpred (x,y)

But A0-A1-A2 should not be confused with macroroles themselves


Generalized Semantic RolesA0 A1 A2 vs Actor Undergoer

Learner /Thing learned

Thing learned /Learner

TeacherEAR(x, )] CAUSE [BECOME know(y,z)]

Thing learnedLearnerENDER

Thing knownKnowerER

A2A1A0

DESSE:Arguments of saber, aprenderand ensear:


GSR and Argument realization

A0 A1 A

DOSubj

2%Other

5%S=0

93%S=1Intransitive: Subj (+ oblique)

10%Other

3 %S=0 D=2

25 %S=0 D=1

61%S=1 D=2

Transitive: Subj DObj (+ oblique)

34%other / not set

30%S=1 D=2 I=3

36%S=0 D=2 I=1

Ditransitive: Subj DObj IObj (+ oblique)Frequency of argument realizations

Active voice

Subject is almost always higherthan DO in the hierarchy of GSRs


GSR and Indirect ObjectsA1 A2

DObj

10%Other

25%S=1 I 2

61%S=2 I = 1

Two participants:Subj IObj (+ oblique)

34%other / not set

30%S=1 D=2 I=3

36%S=0 D=2 I=1

Three participants:Subj DObj IObj (+ oblique)he status of IObj in this hierarchy is

nclear. In schemas, it can be

conceived as a middle (A1) or asan additional (A3) argument

In , IO usually outranks thesubject, as in psychological verbs[A1:Experiencer A2:Stimulus]

A Mara le gusta la msica

"Mary likes music"roblem: the nature of IO and DO


GSR and Argument realization"Inversion (?)"

Psychological verbs (feeling, desire, )

a) : querer, temer, amar, odiar, admirar,Ex: l la quiere "He loves her"

pred'(A1, A2); stative with human EXP as PSA

b) : gustar, interesar, importar, encantar, doler, ..Ex: A ella le gusta "She likes him/her"

pred'(A1, A2); stative with some PSA properties on IO

c) : sorprender, asustar, preocupar, impresionar, Ex: l la impresion "He impressed her"

but there are no clear limits between (b) and (c)


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Psychological verbs and dative case

ercentage of dative case for 3rderson clitic Experiencer in two-articipant clauses with verbs ofeeling'

A Paula le/la alegr la noticia

'The news pleased Paula"

he main conditioning factors

eem to be dinamicity andfectiveness : calmar, for

xample, is more dynamic andfective than tranquilizar (1/6)17%Calmar'calm'

(3/7)43%Consolar'console'

(6/11)55%Tranquilizar'calm'

(4/7)57%Preocupar'worry'

(3/5)60%Distraer'amuse'

(2/3)67%Alegrar'please'

(14/19)74%Sorprender'surprise'

(9/12)75%Impresionar'impress'

(14/15)93%Molestar'bother'

(224/225)100%Gustar'like'


Objects

Subj & DO & IO = direct core arguments

Rough RRG equivalents Subject = PSA DO = Undergoer IO = NMR

Corpus data reveal a continuum DO IO withseveral factors at play: Case: accusative vs dative (3rd person clitic) Preposition a Cliticization and clitic-doubling


Variable case marking

Some Objects are referred by a dative clitic [le(s)] instead of anaccusative clitic [lo(s)/la(s)], even with the same verb and within thesame text

a. El padre le enseaba a conocer las hierbas (Jov: 023)The father taught him [dat] to know about herbs

b.A coserla enseaban desde muy pequea (Usos: 071)She was taught to sew since her early infance

a. Lo que realmente lopreocupaba era.. (Hist: 131)What actually worried him [ac] was

b. Esos bienes que tanto lepreocupan (Hist: 70)These goods that so much worry him [dat]

Le is the canonical form for masculine and feminine Indirect ObjectsR] in ditransitive clauses

Le regal un libro a Mara

n two-participant clauses we can rank the verbs from more dative-likeo less dative-like


Variable object marking

Some Objects are doubled by a cross-referencpronominal clitic

- Conocs a Elena Garro? []- Y de dnde la conocs vos a Elena Garro? (BAIRES:418, 24-

Doubling by clitic is usual with Indirect Objects

Le regal un libro a Mara "I gave Mary a book"

[besides syntactic function, the main conditioning factor is accessibilstatus (Belloro, yesterday)]


Variable object markingSome Objects are marked by preposition a

Encontr a un amigo I met a friend

Encontr un amigo id.

Preposition a is used obligatorily to mark fullndirect Objects

Le regal un libro a MaraI gave Mary a book


3-participantsSubj DO IO

2-participants:

Subj Obj

99.7%0.3%31.1%Dative clitic

[vs Accusative]

42.8%1.0%3.8%Clitic Doubling

[vs (a) NP]

100 %0.7%9.9 %A + NP[vs NP]

R = IOO = DOObject


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truction Ditransitive (Mono)transitive Ditransitive

cipant O P R

NP

non-doubled

accusative

a NP

(doubled)

dative

ctic Function DO IO


0%

20%

40%

60%

80%

100%

% a 100% 100% 100% 90% 42,4% 2,7% 0,4% 0%

% doubling 99,5% 100% 99,2% 14,7% 2,8% 2,7% 0,3% 0,2%

% dative 100% 83% 73% 54% 2,7% 0,2%

1 2 Vd Pro 3 anim def animindef

inan def. inanindef.

Claus

Object variation and the animacy hierarchy


Object variation

No dialect of Spanish has categorical rules for the use of a, cliticdoubling or lesmo. Everywhere we have a gradient

The general tendency is to have unmarked nominals for O inditransitive clauses and for P low in the animacy hierarchy.In general,we have morphologically marked objects for referents high in theanimacy hierarchy (Silverstein 1976)

Other relevant factors (not explored today):

Clitic doubling is also goberned by the animacy hierarchy, butcorrelates more strongly with discourse status: topicality and

accesibility of the referent Case is also governed by dialect variation, gender, and type of

process (dinamicity, effectiveness).


Subject and object in Spanish

Participants in SUBJ-PRED-OBJ[(+Obl)pattern[N=81954clauses]

SUBJ OBJ

Human 80.50 % 27.14 %Agreement/clitic only 63.80 % 25.90 %Definite (if NP) 90.00 % 66.33 %Preverbal (if NP or clause) 73.67% 3.84 %

Participantsin SUBJ-PRED-DO-IO (+Obl) pattern [N = 8455 clauses]

SUBJ DO IOHuman 84.18 % 2.25% 90.24 %

Agreement/clitic only 65.95 % 10.65% 74.14 %Definite (if NP) 90.06 % 53.57% 89.02 %Preverbal (if NP or clause) 74.50 % 2.40 % 9.50 %


Object and markednessTransitive clauses

SUBJECT DIROBJ

Human Non Human

Highly accessible Low accessibility

Definite less definite

Topic (Part of) Rheme[Agent] [Patient]

Objects

(unmarked) (marked)

Non Human Human a-marking, le

Indefinite Definite

Low accessibility More accessible

doubling(Part of) Rheme Topic

Patient Less affected lesmo


ConclusionsADESSE: What is it good for?

ADESSE is, above all, a database for the empirical study the interaction between verbs and constructions in Spanis

Constructional alternatives for a verb, a syntactic function or asemantic role (with frequencies in a corpus)

Verbs and syntactic constructions for a semantic domain Verbs and semantic domains for a particular construction ...

Additionally, it allows the search and study of manyimaginable correlations between syntactic and semanticfeatures (case, person, number, definiteness, tense, mood)


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Conclusions / final remarks

t is necessary to observe (spoken and written)anguage in use and to take into accountfrequency as an important factor of languagestructure and meaning

Many grammatical categories manifest as agradient and not as discrete categories. We haveseen that this is the case with argument structure,

argument realization, and grammatical relations.The task is to identify the factors influencing thechoice of a form, and the strength of each factor


Conclusions / final remarks

It order to achieve descriptive adequacy, we needcorpora annotated with increasingly detailedsyntactic and semantic categories

But the categories used in corpus annotationshould not be taken for granted, and must berevised in the light of corpus evidence

Therefore, we have to move continually fromanalytical categories to corpus and from corpus to

analytical categories

(That is also a disclaimer:Researchers can get adesse data at with somanalysis, but the final analysis of each example is responsibility of the user)


References

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a corpus-based approach to argument structure goals functional

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