HG2002 Semantics and Pragmatics

Meaning Components

Francis BondDivision of Linguistics and Multilingual Studies

http://www3.ntu.edu.sg/home/fcbond/bond@ieee.org

Lecture 9Location: SPMS LT-2

Creative Commons Attribution License: you are free to share and adaptas long as you give appropriate credit and add no additional restrictions:

https://creativecommons.org/licenses/by/4.0/.

HG2002 (2019)

Overview

ã Revision: Speech as Action (skip)

â Austin’s Speech Act Theory (skip)â Categorizing Speech Acts (skip)â Indirect Speech Acts (skip)

ã Componential Analysis

ã Katz’s Semantic Theory

ã Levin’s Verbal Alternations

ã Talmy’s Cognitive Structure

ã Jackendoff’s (Lexical) Conceptual Structure

ã Pustejovsky’s Generative Lexicon

ã Next Lecture: Chapter 10 — Formal Semantics

1

Componential Analysis

HG2002 (2019) 2

Break word meaning into its components

ã For example:

woman [female] [adult] [human]spinster [female] [adult] [human] [unmarried]bachelor [male] [adult] [human] [unmarried]wife [female] [adult] [human] [married]girl [female] [child] [human]boy [male] [child] [human]

semantic components/primitives shown as [component]

Reasons to indulge Componential Analysis:

â components allow a compact descriptionâ interact with morphology/syntaxâ form part of our cognitive architecture

Inspired by work on phonetics in the Prague School 3

Using Lexical Relations to find Components

ã hyponymy

A lexical item P is a hyponym of Q if all the components ofQ are also in P.

woman [female] [adult] [human]spinster [female] [adult] [human] [unmarried]wife [female] [adult] [human] [married]

spinster ⊂ woman; wife ⊂ woman

ã incompatibility

A lexical item P is incompatible with Q if they share somecomponents but differ in one or more contrasting com-ponents

spinster ̸≈ wife

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Binary Features

ã We can make things more economical (fewer components):

woman [+female] [+adult] [+human]spinster [+female] [+adult] [+human] [–married]bachelor [–female] [+adult] [+human] [–married]wife [+female] [+adult] [+human] [+married]girl [+female] [-adult] [+human]

â Which should be +? [+female] or [–male]â Presumably also [–electric], [–conical], …

Only show relevant featuresâ antonyms differ in only one binary component

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Redundancy Rules

ã We can add relations between components:

[+human] → [+animate][+adult] → [+animate][+animate] → [+concrete][+married] → [+adult][+married] → [+human] …

ã Which allows us to write:

woman [+female] [+adult] [+human]spinster [+female] [+adult] [+human] [–married]bachelor [–female] [+adult] [+human] [–married]wife [+female] [+married]

??? Can we say [–married] → [+human]?

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More Complex Breakdowns

ã We can add relations between components:

[+father] → [+male] [+parent][+father](x,y) → [+male](x) [+parent](x,y)[+son](x,y) → [+male](x) [+parent](y,x)[+brother](x,y) → [+male](x) [+parent](z,x) [+parent](z,y)[+grandfather](x,y) → [+male](x) [+parent](x,z) [+parent](z,y)

ã Assume [+parent](x,y) means “x is the parent of y”

ã There are various ways you can formalize such relationships

â Many parts of language can be formalized in such a way

??? Can you do this for demonstratives?this, that, these, those, what, here, there, where

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Katz’s Semantic Theory

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Katz’s Semantic Theory

ã Two Central Ideas:

â Semantic rules must be recursiveto deal with infinite meaning

â Semantic rules interact with syntactic rulesto build up meaning, which is compositional

ã Two major components:

â A dictionary pairing lexical items with semantic representa-tions

â A set of projection rules that show how meaning is built up

‘Sam kissed Kim’ vs. ‘Kim kissed Sam’

Compositional : the meaning of the whole depends only on the meanings of the parts and the method of combination. 9

The dictionary

ã bachelor {N}

1. (human) (male) [one who has never been married]2. (human) (male) [young knight serving under the standard of

another knight]3. (human) [one who has the lowest academic degree]4. (animal) (male) [young fur seal without a mate in the breed-

ing season]

ã (semantic markers) are the links that bind lexical items to-gether in lexical relations

ã [distinguishers] serve to identify this particular lexical itemthis information is not relevant to syntax

Similar to genus and differentiae. 10

Projection Rules

1. Projection rules combine with syntactic rules to produce themeaning of a sentence

ã Information is passed up the tree and collected at the top.â Information is only added, never deletedâ It must come from words or rules (or constructions)

2. Selectional restrictions ⟨⟩ help to reduce ambiguity and limitthe possible readings

ã Accounts for entailment of some (semantic markers)

There is a chair in the room.There is a (physical object) in the room.There is a (piece of furniture) in the room.There is (something having legs) in the room.

More about this in Theories of Syntax/HPSG 11

Selectional restrictions

1. colorful {adj}(a) (color) [abounding in contrast or variety of bright colors)

⟨(physical object) or (social activity)⟩(b) (evaluative) [having distinctive character, vividness or pic-

turesqueness) ⟨(aesthetic object) or (social activity)⟩

2. ball {N}(a) (social activity) (large) (assembly) [for the purpose of

social dancing](b) (physical object) [having globular shape](c) (physical object) [solid missile for project by engine of

war]

ã colorful ball: The selectional restrictions rule out: 1b + 2b, 1b+ 2c

Modern theories prefer selectional preferences: probabilities not categories. 12

Quick Summary

Katz presents some of the earliest efforts in componential se-mantics within generative grammar (through projection rules andselection restrictions).

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Grammatical Rules andSemantic Components

14

Verb Classification

ã We can investigate the meaning of a verb by looking at its gram-matical behavior

(1) Consider the following transitive verbsa. Margaret cut the breadb. Janet broke the vasec. Terry touched the catd. Carla hit the door

ã These do not all allow the same argument structure alternations

(Levin, 1993) 15

Diathesis Alternations

ã Causative/inchoative alternation:

Kim broke the window ↔ The window brokealso the window is broken (state)

ã Middle construction alternation:

Kim cut the bread ↔ The bread cut easily

ã Conative alternation:

Kim hit the door ↔ Kim hit at the door

ã Body-part possessor ascension alternation:

Kim cut Sandy’s arm ↔ Kim cut Sandy on the arm

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Diathesis Alternations and Verb Classes

ã A verb’s (in)compatibility with different alternations is a strongpredictor of its lexical semantics:

break cut hit touchCausative YES NO NO NOMiddle YES YES NO NOConative NO YES YES NOBody-part NO YES YES YES

break = {break, chip, crack, crash, crush, ...}cut = {chip, clip, cut, hack, hew, saw, ...}hit = {bang, bash, batter, beat, bump, ...}touch = {caress, graze, kiss, lick, nudge, ...}

??? Can you give me some other examples?

(Levin, 1993) 17

ã We can analyze components that correlate with the alternations

break cause, changecut cause, change, contact, motionhit contact, motiontouch contact

ã The semantic class/components predicts the syntax of novelwords

ã Not all parts of meaning are relevant to syntaxhas an affect has no affectSemantic Markers Semantic DistinguishersGrammatically Relevant Subsystem Unrestricted Conceptual RepresentationSemantic Structure Semantic ContentSemantic Form Conceptual StructureSemantic Structure Conceptual Structure

(Levin, 1993) 18

Thematic Roles and Linking Rules

ã Semantics-Syntax interface is even more ‘satisfactory’ with the-matic roles

ã Verbs often link their thematic roles to arguments in differentways (locative alternation)

(2) a. He loaded newspapers onto the van ⟨AGENT,THEME⟩

b. He loaded the van with newspapers ⟨AGENT,GOAL⟩

ã But the meanings are not identical: (2b) implies completion,and the theta-grid does not deal with the adjuncts

ã We need more than just theta-grids/roles

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Movement-to-location verbs

ã locative alternation

(3) a. Andy poured oil into the panb. *Andy poured the pan with oil

(4) a. *Andy filled oil into the panb. Andy filled the pan with oil

(5) a. Andy brushed oil onto the panb. Andy brushed the pan with oil

(6) a. ⟨AGENT, THEME, PP:GOAL⟩b. ⟨AGENT, PATIENT/GOAL, PP:INSTRUMENT/THEME?⟩

ã Clearly not all movement verbs can use this alternation

ã How fine-grained should verb classification be?

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Explain with verb classes

ã Verbs of movement: ‘X causes Y to move into/onto Z’

1. Simple motion verbs: put, push2. Manner specified: pour, drip, slosh

X puts Y on Z

ã Verbs of change of state: ‘X causes Z to change state by meansof moving Y into/onto Z’: fill, coat, cover

X fills Z with Y

ã Verbs of movement ‘X causes Y to move into/onto Z’ which alsodescribe a kind of motion which causes an effect on the entityZ: spray, paint (?), brush

X sprays Z with Y

⊗Slightly circular: alternations motivate classes which explain alternations 21

Componentsand Conflation Patterns

22

Cognitive Semantics

ã Research programme by Talmy (similar to Levin’s & Pinker’s)

ã Major semantic components of Verbs of Motion:â Figure: object moving or located with respect to the groundâ Ground: reference objectâ Motion: the presence of movement or location in the eventâ Path: the course followed or site occupied by the Figure w.r.t.

the Ground.â Manner: the type of motion

(7) KimFigure

swamManner

away fromPath

the crocodileGround

(8) The bananaFigure

hungManner

fromPath

the treeGround

ã English: Manner in verb, Path as adjunct

(Talmy, 2000) 23

? ? ? ? ?

ã Find: Figure? Ground? Path? Manner?

(9) The bottle floated into the cave

(10) They rolled the keg into the party

ã How about Motion? (where is Talmy’s Motion component?)

24

Different Lexicalizations of Movement

(11) The bottle floated into the cave(12) They rolled the keg into the party

ã These are lexicalized differently in different languages.

ã Spanish: Path in verb, Manner as adjunct

(13) Lathe

botellabottle

entrómoved-in

ato

lathe

cuevacave

flotandofloating

“The bottle entered the cave, floating”(14) Metí

I-moved-inelthe

barrilbarrel

ato

lathe

bodegastoreroom

rodandolorolling-it

“I put the keg into the storeroom, rolling (it)”

??? What’s the difference?

25

Typology of Motion in Languages

Language (Family) Verb Conflation PatternRomance, Semitic, Polynesian, … Path + fact-of-MotionIndo-European (− Romance), Chinese Manner/Cause + fact-of-MotionNavajo, Atsuwegei, … Figure + fact-of-Motion

ã verb-framed (Motion with Path)

ã satellite-framed (Motion with Manner)

??? Which group is Japanese from?

(15) 樽をtaru-wobarrel-acc

倉庫にsouko-nistoreroom-to

転がしてkorogasiterolling

⼊れたiretaput-in

“I put the keg into the storeroom, rolling”

HG2002 (2019) 26

Quick Summary

Katz presents some of the earliest efforts in componential se-mantics within generative grammar (through projection rules andselection restrictions).

With Levin, Pinker, and Talmy (the last two sections) we lookedat how certain semantic theories argue the interdependence be-tween semantics and syntax (i.e. how sematic components arenecessary for the proper decription of syntactic processes).

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Break

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Jackendoff’sConceptual Semantics:

Lexical ConceptualStructure

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Describing Mental Representations

ã An attempt to explain how we think

ã Mentalist PostulateMeaning in natural language is an information structurethat is mentally encoded by human beings – so, describingmeaning involves describing mental representations;

ã The goal is to capture generalizations:

x lifted y entails y rosex gave z to y entails y received zx persuaded y that P entails y came to believe P

x cause E to occur entails E occurs

ã There should be a component cause in these and many otherlexical items

(Jackendoff, 1990, 1997) 30

Semantic Components

ã Universal Semantic Categories/Concepts

â Event, State [the basic conceptual situations]â Material Thing/Object, Path, Place, Property

(16) a. [S [NP Bobby] [V P [V went] [PP [P into] [NP thehouse]]]]

b. [Event GO ([Thing BOBBY], [Path TO ([Place IN([Thing house])])])]

ã focus is Motion – ‘house’ is not fully analyzed

ã Jackendoff also works under the assumption that Syntax andSemantics constrain one another

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Motion as a tree

(17) Bobby went into the house

(18) [Event GO ([Thing BOBBY], [Path TO ([Place IN ([Thing

house])])])]

(19) “Bobby traverses a path that terminates at the interior ofthe house”

(20) Event

GO Thing

BOBBY

Path

TO Place

IN Thing

HOUSE

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Location

(21) The car is in the garage

(22) [State BELoc ([Thing CAR], [Place IN ([Thing GARAGE])])]

(23) “The car is in the state located in the interior of the garage”

(24) State

BE-LOC Thing

CAR

Place

IN Thing

GARAGE

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Extend Location in three ways

ã Location is also used, among others, to ascert properties (inconjunction with a special BEIdent)

Semantic Field BE (state) GO (event)spatial location Jo is in the club Alex went into the housetemporal location The exam is on Wednesday The exam moved to Thursdayproperty ascription The class is full The class went from full to emptypossession This theory belongs to Ann Elk The prize went to JC

(25) a. The pool emptiedb. [Event INCH ([State BE-IDENT ([Thing POOL], [Place AT

([Property EMPTY])])])](26) a. Sandy emptied the pool

b. [Event CAUSE ([Thing SANDY], [Event INCH ([State BE-IDENT ([Thing POOL], [Place AT ([Property EMPTY])])])])]

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Structure of Events

ã The structure of events and states can be represented as beingformed by rules

[EVENT] −→ [Event GO ([THING], [PATH])]

[STATE] −→ [State BE ([THING], [PLACE])]

[EVENT] −→ [Event CAUSE ([THING], [EVENT])]

[EVENT] −→ [Event INCH ([STATE])]

[PATH] −→ [TO ([PLACE])]

[PLACE] −→ [IN ([THING])]

[PLACE] −→ [AT ([TIME])]

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THING: Boundedness and Internal Structure

ã Two semantic features of [THING]:

Boundedness Internal Struct. Type Example+b −i individuals a dog/two dogs+b +i groups a committee−b −i substances water−b +i aggregates dogs, cattle

ã Boundedness:whether a noun is count or mass (if you split a dog in half youdon’t get two instances of dog)

ã Internal Structure:whether a noun is divisible/contains individual units

ã Two binary features generate four classes of nouns

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Cross-category Generalizations

ã This can be extended to verb aspect (the verb event is also[±b])

ã In verbs, [±b] is used to differentiate actions bound in time

ã This shows syntactic interaction

(27) Bill ate two hot dogs in two hours.(28) *Bill ate hot dogs in two hours.(29) #Bill ate two hot dogs for two hours.(30) Bill ate hot dogs for two hours.

ã sleep [−b], cough [+b], eat [±b]durative adverbials with bounded verbs generate iterative in-terpretations (and vice-versa)

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Conversion: Boundedness and Internal Structure

ã Including

plural [+b, –i] → [–b, +i] brick → brickscomposed of [–b, +i] → [+b, –i] bricks → house of bricksuniversal packager [–b, –i] → [+b, –i] coffee → a (cup of) coffee

ã Excluding

element [–b,+i] → [+b, –i] grain of ricepartitive [–b, ±i] → [+b, –i] top of the mountain,

one of the dogsuniversal grinder [+b, –i] → [–b, –i] There’s dog all over the road

See Bond (2005) for an extension to Japanese and computational implementation. 38

Quick Summary

Katz presents some of the earliest efforts in componential se-mantics within generative grammar (through projection rules andselection restrictions).

With Levin, Pinker, and Talmy (the last two sections) we lookedat how certain semantic theories argue the interdependence be-tween semantics and syntax (i.e. how sematic components arenecessary for the proper decription of syntactic processes).

Jackendoff, much like Levin, Pinker, and Talmy, uses lexicaldecomposition to investigate the semantics-grammar interface.But goes one step further by proposing ‘conceptual structures’ thathe believes underlie linguistic behaviour.

HG2002 (2019) 39

Pustejovsky’sGenerative Lexicon

40

The Generative Lexicon

ã This brings in more encyclopedic knowledge

ã Each lexical entry can have:argument structureevent structurelexical inheritance structure (lexical network)qualia structure (further lexical properties):

constitutive constituent partsformal relation to other thingstelic purposeagentive how it is made

ã Interpretation is generated by combining word meanings

Pustejovsky (1995) 41

The ideas behind the Generative Lexicon

ã (often) Computationally tractable

ã Lexical network that encodes some information

ã Word meaning is decomposed, so that it can be composed withother words

ã The range of composition teaches us something about the in-ternal structure of the word

â Rich Representation: lexical decompositionâ Rich Rules: coercion, sub-selection, co-composition

HG2002 (2019) 42

Event Structure

ã Events have complex structure(can be composed of smaller sub-events)

â State S

e

understand, love, be tallâ Process P

e1 …en

sing, walk, swimâ Transition T

E1 ¬E2

open, close, buildFor an achievement, typically E1 = ¬e1; E2 = e1

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Different Alternations

(31) The door closed T

P

[¬ closed(door)]

S

[closed(door)]

(32) Jamie closed the door T

P

[act(j, door) ∧ ¬ closed(door)]

S

[closed(door)]

(33) The door is closed S

e

[closed(door)]

ã Causative and Inchoative are represented by transition (T) –the difference is in the recognition of the acting agent

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Modifier Ambiguity

ã Complex Event Structure is also motivated by ambiguity

(34) Jamie closed the door rudelya. Jamie closed the door in a rude way [with his foot]

T

P [rude(P)]

[act(j, door) ∧ ¬ closed(door)]

S

[closed(door)]

b. It was rude of Jamie to close the doorT [rude(T)]

P

[act(j, door) ∧ ¬ closed(door)]

S

[closed(door)]

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Lexicon and Meaning

Pustejovsky claims:

ã Just listing senses of words is not enough

ã It goes against general reasoning

ã Inferences must rely on linguistic information

ã Meaning composition must be done through available proper-ties in the lexical items

These properties are called: Qualia (all words have it)

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Qualia Structure in Nouns

ã Links to a concept in a lexical network

ã formal properties, e.g. human, animal, yellow

ã telic properties, e.g. links to the event ’to type’

ã typist

argstr[arg1 x:C123(typist,typewriter operator)

]qualia

formal[x [ ⊂ person ]

]telic

[type(e,x)

]

See Bond and Paik (1997) for an account of numeral classifiers using the GL 47

Qualia Structure and Modifier Ambiguity

(35) fast typista. a typist who is fast [at running]b. a typist who types fast

ã typist

argstr[arg1 x:C123(typist,typewriter operator)

]qualia

formal[x [ ⊂ person ]

]telic

[type(e,x)

]

ã (35a) fast modifies x

ã (35b) fast modifies e

HG2002 (2019) 48

Quick Summary

Katz presents some of the earliest efforts in componential se-mantics within generative grammar (through projection rules andselection restrictions).

With Levin, Pinker, and Talmy (the last two sections) we lookedat how certain semantic theories argue the interdependence be-tween semantics and syntax (i.e. how sematic components arenecessary for the proper decription of syntactic processes).

Jackendoff (much like Levin, Pinker, and Talmy) uses lexicaldecomposition to investigate the semantics-grammar interface.But goes one step further by proposing ‘conceptual structures’ thathe believes underlie linguistic behaviour.

Pustejovsky extents Jackendoff compositional representation,and incorporates general/encyclopaedic knowledge that is bettersuited to deal with nuanced interpretations (e.g. modification).

HG2002 (2019) 49

Problems with Components of Meaning

ã Primitives are the same as necessary and sufficient conditionsit is impossible to agree on the definitions, or to validate thembut they allow us to state generalizations better

ã No proposed set can capture all aspects of meaning

ã It is just markerese which still needs to be explained, there isno grounding (using words to define words is circular)

ã Psycho-linguistic evidence is weak

ã Recent work replaces components with inheritance or dimen-sions

â boy1 ⊂ male1 ∧ ⊂ child1

â boy1 near male1 on some dimensions; near child1 on othersâ same generalizations, more psychologically plausible

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Conclusion

ã Meaning can be broken up into units smaller than words: com-ponents

â These can be combined to make larger meaningsâ At least some of them influence syntaxâ They may be psychologically realâ Many parts of meaning can be treated in this way

ã Note: Selectional restrictions are too strict, selectional prefer-ences (giving prototypical arguments and measuring the simi-larity) are more common in modern approaches:assigning probabilities to interpretations

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Assignment 2ã Due November 7th

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Fry & Laurie: Language

ã Series 1 Episode 2http://abitoffryandlaurie.co.uk/sketches/language_conversation

ã Series 2 Episode 6http://abitoffryandlaurie.co.uk/sketches/beauty_and_ideas

ã Stephen Fry on Languagehttp://www.stephenfry.com/2008/11/04/dont-mind-your-language%E2%80%A6/

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Bibliography

Francis Bond. 2005. Translating the Untranslatable: A solution to the Problemof Generating English Determiners. CSLI Studies in Computational Linguis-tics. CSLI Publications.

Francis Bond and Kyonghee Paik. 1997. Classifying correspondence inJapanese and Korean. In 3rd Pacific Association for Computational Lin-guistics Conference: PACLING-97, pages 58–67. Meisei University, Tokyo,Japan.

Ray Jackendoff. 1990. Semantic Structures. MIT Press, Cambridge, MA.

Ray Jackendoff. 1997. The Architecture of the Language Faculty. MIT Press,Cambridge, MA.

Beth Levin. 1993. English Verb Classes and Alternations. University of ChicagoPress, Chicago, London.

James Pustejovsky. 1995. The Generative Lexicon. MIT Press, Cambridge,MA.

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Leonard Talmy. 2000. Toward a Cognitive Semantics. MIT Press.

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