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When Compositionality Fails to Predict Systematicity. Reinhard Blutner, Petra Hendriks, Helen de Hoop, Oren Schwartz.

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when compositionality fails to predict systematicity

When Compositionality Fails to Predict Systematicity

Reinhard Blutner, Petra Hendriks,

Helen de Hoop, Oren Schwartz

the immediate appeal of compositionality frege 1923
It is astonishing what language can do. With a few syllables it can express an incalculable number of thoughts, so that even a thought grasped by a terrestrial being for the first time can be put into a form of words which will be understood by

someone to whom the thought isentirely new. This would be impossible, were we not able to distinguish parts in the thoughts corresponding to the parts of a sentence, so that the structure of the sentence serves as the image of the structure of the thoughts.

The immediate appeal of compositionality: Frege (1923)
compositionality
Compositionality

The meaning of a complex expression is determined by its structure and the meanings of its constitutents.

equivalently

There is a homomorphism between the syntactic term algebra to the algebra of meanings.

compositionality4
Compositionality

Compositionality is necessary to explain the productivity of language.

Compositionality entails productivity.

systematicity
Systematicity
  • The term and empirical hypothesis was introduced by Fodor & Pylyshyn (1988), who didn’t attempt a precise definition of the concept or a complete description of the empirical phenomenon.
  • Van Gelder & Niklasson (1994) summarize F&P’s notion of systematicity as: [the] ability to do some things of a given cognitive type (including at least “thinking a thought” and making an inference) is intrinsically connected with their ability to do other, structurally related things of that type.
systematicity6
Systematicity

When an agent understands the expressions brown triangle and black square, she understands the expressions brown square and black triangle as well.

Does compositionality entail systematicity?

a classical example
A Classical Example
  • Agent understands brown triangle and black square.
  • She constructs the conceptual representations BROWNTRIANGLE and BLACKSQUARE (via compositionality).
  • She knows the truth conditional impact of the corresponding constitutents, and she extracts the lexicon entries: brown -> BROWN, square->SQUARE, etc.
  • Using these, she constructs BROWNSQUARE and BLACKTRIANGLE (via compositionality)
  • Thus compositionality may derive systematicity
systematicity8
Systematicity

If an agent understands

within an hour and without a watch,

does she also understand

within a watch and without an hour?

(Szabo 2004)

our view
Our View
  • Language is (mostly) systematic and compositional, but not always.
  • Traditional semantic analyses have difficulty with cases where the systematicity of meaning is weak or missing.
  • Connectionist models are well suited to handling these types of cases, and can account for the semantic contribution of a constitutent that is both systematic (in general) and idiosyncratic (in certain cases).
why compositionality fails to explain systsematicity
Why compositionality fails to explain systsematicity
  • In his “Grundlagen der Mathematik” Frege (1884) noticed the context-dependence of words (and took this as an argument against compositionality in NL)

“One should ask for the meaning of a word only in the context of a sentence, and not in isolation.“

empirical phenomena
Empirical Phenomena
  • Quine (1960) was the first who noted the contrast between red apple (red on the outside) and pink grapefruit (pink on the inside).
  • Lahav (1993) argues that an adjective such as brown doesn’t make a simple and fixed contribution to any composite expression in which it appears:

brown cow, brown crystal, brown book, brown newspaper

empirical phenomena12
Empirical Phenomena
  • Different colors typically denoted by red in red apple and red hair.

the actual color value deviates in a systematic way from the prototypical color value that can be assigned to the color adjective in isolation – in dependency on the conceptual properties of the modified noun

  • Similarly, the same color is often described with different adjectives

In Japanese, brown sugar, aka-zatoo (lit. ‘red sugar’) comes in the same range of colors as shira-miso, (lit. ‘white bean paste’)

three consequences
Three consequences
  • Intersectivity, ||A(B)|| = ||A(x)||||B||, doesn’t hold, even for most ‘absolute’ adjectives
  • Systematicity statements cannot be derived from compositionality in these cases
  • Encyclopedic knowledge is required to determine the truth conditional content of an utterance (explicature in Relevance Theory).
a related phenomenon
A Related Phenomenon
  • Typicality

A specific instance of a red apple is more typical of a “red apple” than of an “apple”

  • Incompatible Conjunctions

The typicality effects are greater for “incompatible conjunctions” (striped apple) than for “compatible conjunctions” (green apple)

a concrete question
A Concrete Question
  • How should we account for the semantic contribution of an (absolute) adjective to an (Adjective Noun)N complex expression in the face of these phenomena?
radical underspecification with contextual enrichment
Radical underspecificationwith contextual enrichment
  • smallx small(x,N) *
  • small terrier x [small(x,N) & terrier(x)]

Analogously for red apple with place-holders for the relevant parts

  • red  x [part(Y,x) & red(Y)]
  • red apple x [part(Y,x) & red(Y) & apple(x)]

How to determine the proper values for N and Y, respectively?

    • Contextual enrichment, as in Probabilistic Theory of Relevance (van Rooy 2000)

* with small(x,N)  size(x) < N

problems with underspecification
Problems with underspecification
  • Does not really clarify how to determine the border line between the underspecified representation and the contextual enrichment
  • It is difficult to see how the available mechanisms account for the prototype effects found in adjectival modification
a connectionist approach
A connectionist approach

Inspired by the (symbolic)

selective modification model

(Smith, Osherson, Rips & Keane 1988)

  • Prototype representations consisting of
    • Symbolic, structured concepts
    • Attribute-value pairs, weighted by salience
  • Modifiers act on prototypes by increasing salience of attribute and changing its value
  • Tversky’s (1977) contrast rule for similarity
a connectionist approach19
A connectionist approach

Adjective

Noun

Conceptual Layer

a connectionist approach20
A connectionist approach

Adjective

Noun

Conceptual Layer

Color

a connectionist approach21
A connectionist approach

Adjective

Noun

Conceptual Layer

Taste

a connectionist approach22
A connectionist approach

Adjective

Noun

Conceptual Layer

Peel

a connectionist approach23
A connectionist approach

Adjective

Noun

Pulp

Conceptual Layer

a connectionist approach24
A connectionist approach

Adjective

Noun

(Color x Peel)

Conceptual Layer

Peel

Color

a connectionist approach25
A connectionist approach

Adjective

Noun

Conceptual Layer

red

a connectionist approach26
A connectionist approach

Adjective

Noun

Conceptual Layer

white

a connectionist approach27
A connectionist approach

Adjective

Noun

white pulp

red peel

Conceptual Layer

red

a connectionist approach28
A connectionist approach

Adjective

Noun

Conceptual Layer

a connectionist approach29
A connectionist approach

Adjective

Noun

Conceptual Layer

a connectinist approach
A connectinist approach
  • Default uniform connections within conceptual layer
  • In training, instances are presented at the conceptual layer and at the (localist) adjective and noun layers.
  • The prototypes learned by the model are found by turning on units in the adjective and noun layers and letting the network settle into a representation at the conceptual layer.
prototype effects
Prototype effects
  • Using Tversky's (1977) contrast rule (formulated for activation vectors) sim(s,t) = i min(si,ti) i |siti|
  • sim(sred apple,t1) > sim(sapple, t1)
  • sim(spurple apple,t2)sim(sapple,t2)

> sim(sred apple,t1)sim(sapple,t1)

t1= a red apple, t2 = a purple apple

conclusions
Conclusions
  • Compositionality alone is not formally restrictive enough to explain the type of productivity in NL
  • Semantic contributions of constituents to their complex expressions are more complex and less systematic than we might expect
  • Encyclopedic knowledge is necessary to account for the variability in the semantic contribution of constituents to complex phrases
  • Connectionist approaches easily handle the accumulation and application of this knowledge.