Westerbeek, Koolen & Maes (2015): Stored Object Knowledge and the Production of Referring Expressions #
This file formalizes the computational claim of [WKM15]. In two
production experiments, speakers referring to an object whose type alone distinguishes it from
the distractors mention its color more often the less typical that color is for the object,
and more so for objects whose shape is less diagnostic, which the paper attributes to a
contrast with the color stored with the object's category. The paper argues that models of
content determination without object knowledge cannot capture this: [DR95]'s
Incremental Algorithm, which considers attributes in a fixed preference order and keeps one
only when it rules out a remaining distractor, produces the bare head noun whenever the type
distinguishes the referent, whatever the colors in the scene
(flat_makeReferringExpression_type), so its output for a yellow and a red tomato is the same
(makeReferringExpression_congr_type) and its color-mention rate cannot vary with typicality
(decision_rule_not_ia).
Implementation notes #
The scenes are the flat domains of the Incremental Algorithm's user model, in which the user knows a property exactly when the scene has it. The paper's decision rule, that the probability of mentioning a property rises with its contrast to stored knowledge, is a strictly decreasing rate in the typicality score; the experiments' rates and regression coefficients are reported in the paper and not formalized.
References #
The Incremental Algorithm on a type-distinguished referent #
When the referent's type rules out every distractor and type heads the preference order, the Incremental Algorithm returns the bare head noun, whatever the other attributes hold.
Two scenes with the same types produce the same expression: the algorithm is blind to the colors.
The scene of Figure 1 #
Equations
- WesterbeekKoolenMaes2015.instDecidableEqObject x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
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- One or more equations did not get rendered due to their size.
Instances For
Equations
Types and colors.
- tomato : ObjectValue
- pineapple : ObjectValue
- cucumber : ObjectValue
- red : ObjectValue
- yellow : ObjectValue
- green : ObjectValue
Instances For
Equations
- WesterbeekKoolenMaes2015.instDecidableEqObjectValue x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
Equations
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- One or more equations did not get rendered due to their size.
Instances For
The scene, with the tomato in a given color.
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- One or more equations did not get rendered due to their size.
- WesterbeekKoolenMaes2015.scene tomatoColor WesterbeekKoolenMaes2015.Object.tomato DaleReiter1995.Attr.type = some WesterbeekKoolenMaes2015.ObjectValue.tomato
- WesterbeekKoolenMaes2015.scene tomatoColor WesterbeekKoolenMaes2015.Object.tomato (DaleReiter1995.Attr.property Degree.PropertyDomain.color) = some tomatoColor
- WesterbeekKoolenMaes2015.scene tomatoColor WesterbeekKoolenMaes2015.Object.pineapple DaleReiter1995.Attr.type = some WesterbeekKoolenMaes2015.ObjectValue.pineapple
- WesterbeekKoolenMaes2015.scene tomatoColor WesterbeekKoolenMaes2015.Object.cucumber DaleReiter1995.Attr.type = some WesterbeekKoolenMaes2015.ObjectValue.cucumber
- WesterbeekKoolenMaes2015.scene tomatoColor WesterbeekKoolenMaes2015.Object.cucumber (DaleReiter1995.Attr.property Degree.PropertyDomain.color) = some WesterbeekKoolenMaes2015.ObjectValue.green
- WesterbeekKoolenMaes2015.scene tomatoColor x✝¹ x✝ = none
Instances For
Color first or type first, the algorithm says the tomato of the yellow tomato as of the red one.
The decision rule #
The paper's decision rule: the rate of mentioning a color falls strictly with the color's typicality score for the object.
Equations
- WesterbeekKoolenMaes2015.DecisionRule rate = StrictAnti rate
Instances For
A constant rate, the Incremental Algorithm's, does not follow the rule.