Corpus Approach vs. Generative Approach

and

Movement vs. Grammatical Functions

One-Soon Her

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OUTLINE

1) Contrasting GA and CA

2) Contrasting LFG and TG

3) Conclusion

1) Contrasting GA and CA

What is the ultimate goal of

a generative syntactic theory?

To account for the universal properties and variations in the

syntactic phenomena in all languages, in the simplest way.

A.2

What is the ultimate goal of

a corpus-based syntactic theory?

To discover generalizations and variations in the syntactic

phenomena from the corpus materials at hand.

Let’s see a simple

non-linguistic demonstration

of CA vs. GA

Driving on Planet Earth

Research Goal:

to come up with a description of

the side of the road to drive on,

on Planet Earth

Corpus Approach

“Look and see”

Solution (1):

Australia left

China right

Singapore left

Taiwan right

USA right

etc.

Evaluating Corpus Solution (1)

Not happy

Must make generalizations

Corpus Approach, Solution (2)

Generalization: in some countries, drive on the left; in others, drive on the right.

Australia left

China right

Singapore left

Taiwan right

USA right

etc.

How about the generative approach?

The generative approach assumes:

1) there are universal principles

2) variation is due to parameters

Generative Approach

Solution (1):

Australia left

China right

Singapore left

Taiwan right

USA right

etc.

Evaluating Solution (1)

What’s the predictive power?

Does it rule out the following?

Country X middle

Country Y AM-left/PM-right

Country Z Men-left/Women-right

Evaluating Solution (1)

Each listing is a stipulation, thus no predictive power.

Must generalize and make predictions!

Generative Approach, Solution (2)

Principle: within a country, drive on x side only.

Parameter: x = left/rightAustralia x = left

China x = right

Singapore x = left

Taiwan x = right

USA x = right

etc.

Evaluating Generative Solution (2)Pretty good, but….

1) each listing still a stipulation

2) a parameter always a disjunction

Evaluating Generative Solution (2)Research question: can we get rid of the parameter and the listings?

The research is now theory-driven, rather than data-driven, as the data have been accounted for.

Evaluating Generative Solution (2)

Expanding the scope of data:

side of the road + side of the driver

Driving onthe Left

Right

Driving onthe Right

Left

The driving side is always the opposite of the driver side!!

Generative Approach, Solution (3)

Principle: on Planet Earth, drive on the left, if the driver seat is on the right; otherwise, drive on the right.

Evaluating Generative Solution (3)

Wow, no listings and no parameters!!

But, wait!

There’s still a disjunction.

Evaluating Generative Solution (3)Principle: on Planet Earth, if the driver seat is on the right, then drive on the left; otherwise, drive on the right.

Evaluating Generative Solution (3)

Let’s again expand the scope of data:

driver + passenger + center of the road

Right

Left

The driver is always closer to the center of the road!!

Generative Approach, Solution Ultimate

Principle: when driving on Planet Earth, stay closer to the center of the road in relation to the front seat passenger.

Evaluating GG Solution UltimateDoes it allow a functional explanation?

Yes, it does!Being closer to the center of the road affords

the driver the best range of vision with the least physical strain

Evaluating GA Solution Ultimate

It’s simple and elegant,

but is it complete?

Evaluating GG Solution UltimateConsider

建國高架橋下迴轉道US Postman’s jeep

And, of course, Myanmar!

Evaluating GG Solution Ultimate

…the two kinds of linguists need each other. Or better, that the two kinds of linguists, wherever possible, should exist in the same body. (Fillmore 1992:35)

Evaluating GG Solution Ultimate

Lessons from Myanmar and Pirahã.

Evaluating GG Solution Ultimate

It’s simple and elegant,

but how many countries do you really need to observe to derive it?

2) Contrasting LFG and TG1. Motivation

2. Phrase structures

3. Grammatical features

4. Theta roles & linking

5. Summary & examples

1. Motivation

Under the Generative Grammar, there are many competing frameworks:

TG (incl. GB, MP…)

LFG

HPSG

etc.

They share the same goal, but differ in: 1) what is “simple” exactly?

2) the right balance between descriptive adequacy and theoretical elegance

Consequence:

somewhat different architectures

some different primitive notions

2. Phrase Structures

a.k.a. c(onstituent)-structures

TGPrinciples: X-bar scheme for DS

(spec rule) XP → YP, X’

(comp rule) X’ → ZP, X

Parameters:

(spec rule) YP > X’ or X’ > YP

(comp rule) ZP > X or X > ZP

Extremist View (Kayne 1994) :

Universal X-bar scheme with fixed order:

spec > head > complement

No PS parameters in DS!

TG

DS → movements → SS

TG

That, I don’t know t.

John was kisses t.

LFG Single level c-structure

Language-specific PSR allowed

X-bar scheme as default

LFG

That, I don’t know.

John was kisses.

No DS, no movements. WYSIWYG.

3. Grammatical Features

e.g., case, number, person, etc.

TGFeatures grow on trees.

Mary has kissed John [3/sg/nom] [3/sg/nom] …. …..

LFGFeatures & Grammatical Functions form an

independent f-structure

C-structure

Mary has kissed John

4. Theta roles & linking

TGTheta roles are assigned to tree positions.

kiss [x y]

Mary has kissed John

LFGTheta roles, or argument roles, also form an

independent a-structure,

which is linked with the predicate’s f-structure

kiss <x y>

5. Summary & examples

TG (1) John, Mary has kissed.

kiss [x y]

DS

Mary has kissed John 3/sg/nom 3/sg/nom …. …..

TG (2) John, Mary has kissed.

Movements

John

Mary has kissed t 3/sg/nom 3/sg/nom …. …..

TG (3) John, Mary has kissed.

John

Mary has kissed t [3/sg/nom] [3/sg/nom] …. …..

Feature checking

TG (4) John, Mary has kissed.

SS

John

Mary has kissed t

LFG (1) John, Mary has kissed.

c-structure

John ….

Mary has kissed ….

LFG (2) John, Mary has kissed.

kiss <x y>f-structure

TG vs. LFG

In a nutshell (1)

TG LFG

Movements Yes No

Grammatical functions

No Yes

TG vs. LFG

In a nutshell (2)

TG: tree-centric

theta roles and grammatical features are all part of the tree

LFG: parallel planes

argument structure, functional structure, and constituent structure are all independent

An Overview of LFG1. Lexical entries

2. Phrase structure rules

3. C-structure

4. F-structure

5. Correspondence between

c- and f-structure

1. Sample lexical entries

time N

flies V

2. Sample phrase structure rules

S → NP: SUBJ VP

VP → V NP: OBJ

NP → N

3. Sample c-structure

S NP:SUBJ VP

N V

time flies

4. Sample f-structure

S NP:SUBJ VP

N V

time flies

5. Correspondence between c- and f-structure

S NP:SUBJ VP

N V

time flies

Some of LFG’s Motivations

1. Lexical integrity

2. Non-configurationality

3. Movement paradoxes

4. Lexical processes over movements

1. Lexical Integrity

Lexical Integrity Hypothesis (Huang 1984)

No phrase-level rule may affect

a proper subpart of a word.

Ex: I like singing and dancing →

*I like [sing and dance]-ing.

You speak and I do too. →

*He is a singer and I do too.

TGMary went.

Mary /ed/ go Affix Hopping

Violating lexical integrity.

LFGMary went.

Mary went

Maintaining lexical integrity.

2. Non-configurationality

English is a configurational language, where grammatical relations (e.g., SUBJ, OBJ) are largely encoded by the configuration of the constituent structure.

There are, however, non-configurational languages, where grammatical relations are largely encoded by morphological means.

Language Typology 101

Vi: S

Vt: A P

Vi: S

Vt: A P

Case can be marked

structurally or morphologically!

→ Accusative

→ Nominative (unmarked)

language

Ergative language

→ Absolutive (unmarked)

English

Subj Obj

Mary has kissed John

John has kissed Mary

Case marked by structural configuration.

Malayalam

Case marked by affixes.

Yes, I speak Malayalam.

Malayalam

1. Kutti aana-ye kantu (SOV) child.NOM elephant-ACC saw2. kutti kantu aana-ye (SVO)3. aana-ye kutti kantu (OSV)4. aana-ye kantu kutti (OVS)5. kantu kutti aana-ye (VSO)6. kantu aana-ye kutti (VOS)

Case marked by affixes.

ψ

Malayalam

(TG)

kutti aana-ye kantu

(LFG)

kutti aana-ye kantu

Which is simpler?

(lots of movements!)

(fixed DS, fixed order)

(no DS, no ordering)

(no movements!)

Malayalam

F-structure for all six word orders

Warlpiri

The two small children are chasing that dog.

wita-jarra- kurdu-jarra-small-DUAL-ERG child-DUAL-ERG

ka-pala wajili-pi-nyi pres-3duSUBJ chase-NPAST

yalumpu malikithat.ABS dog.ABS

rlu rlu

ψ ψ

Warlpiri

Word order: Free

Constraints: 1) 1st position must be a constituent

2) 2nd position must be T (AUX)

Examples:

1) [that.ABS dog.ABS]NP T chase children-ERG small-ERG

2) [dog.ABS]N T children-ERG chase small-ERG that.ABS

3) [chase]V T children-ERG dog.ABS small-ERG that.ABS

4) *[T]T chase small-ERG children-ERG that.ABS dog.ABS

5) *[small-ERG dog.ABS]*C T chase children-ERG that.ABS

WarlpiriTG (same as English)

NP

T VP

Consequence: lots of movements

Prediction: Warlpiri, like Eng, has VP

Test: [chase dog.ABS]VP T children-ERG

Result: Warlpiri has no VP!*

Warlpiri

LFG TP → C T C*

C T C ...

Typology: X-bar vs. W-star

Cause: morphology competes with syntax

3. Movement paradoxes

1.a. *The theory does explain.

b. The theory does explain that mass is energy.

c. That mass is energy, the theory does explain t .

2.a. *The theory does capture.

b. *The theory does capture that mass is energy.

c. That mass is energy, the theory does explain t .

3. Movement paradoxes

1.a. You are not a student.

b. Are you not a student?

c. You aren’t a student.

d. Aren’t you a student?

2.a. I am not a student.

b. Am I not a student?

c. *I aren’t a student.

d. Aren’t I a student?

3. Movement paradoxes

1.a.* 他最擅長 .

b. 他最擅長語言學 .

c. 語言學，他最擅長 t .

2.a.* 他最拿手 .

b.* 他最拿手語言學 .

c. 語言學，他最拿手 t .

3. Movement paradoxes

TG: mismatches are unexpected, because the source and the target of movement must be identical.

LFG: mismatches are expected, because there is no movement and mapping between two planes (e.g., c- and f-structure) is not one-to-one.

4. Lexical processes over movements

Participle verbs (present, perfect, passive) in English may convert to adjectives.

1. a very disturbed market. (passive)

2. a well-prepared student. (perfect)

3. an all smiling bride. (present)

Particle V<x> → A<x>

4. Lexical processes over movements

happy [x]

TG

was happy John

Prediction: V[x] → A[x], x undergoes movement

4. Lexical processes over movements

True for passive and unaccusative verbs

disturbed [x y]

TG

was disturbed the market

4. Lexical processes over movements

Not true for unergative verbs

prepared [x]

TG

John has prepared well

V[x] → A[x], x undergoes no movement

4. Lexical processes over movements

happy <x>

LFG <SUBJ>

John was happy

Prediction: V[x] → A[x]

4. Lexical processes over movements

True for all intransitive participle verbs.

disturbed <x y>

LFG

The market was disturbed

<SUBJ>

3) CONCLUSION

The air-mattress metaphor

Corpus Approach vs. Generative Approach

and

Movement vs. Grammatical Functions

One-Soon Her

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