Publication | Closed Access
Feature Indeterminacy and Feature Resolution
252
Citations
18
References
2000
Year
EngineeringSemanticsSyntaxImage AnalysisData SciencePattern RecognitionComputational LinguisticsGrammarLanguage StudiesSyntactic FeaturesFormal SemanticsMachine VisionGrammatical FormalismComputer ScienceFeature ResolutionFeature ConstructionFeature ScalingCategorial GrammarComputer VisionFeature IndeterminacyAutomated ReasoningFormal MethodsImage ResolutionUnification GrammarLinguisticsComputational Semantics
Syntactic features like CASE, PERSON, and GENDER are often assumed to have simple atomic values that are checked for consistency by the standard predicate of equality. The CASE feature has values such as NOM or ACC, and values like MASC and FEM are assumed for the feature GENDER. But such a view does not square with some of the complex behavior these features exhibit. It allows no obvious account of FEATURE INDETERMINACY (how a particular form can satisfy conflicting requirements on a feature like CASE), nor does it give an obvious account of FEATURE RESOLUTION (how PERSON and GENDER features of a coordinate noun phrase are determined on the basis of the conjuncts). We present a theory of feature representation and feature checking that solves these two problems, providing a straightforward characterization of feature indeterminacy and feature resolution while sticking to structures and standard interpretations that have independent motivation. Our theory of features is formulated within the LFG framework, but we believe that similar solutions can be developed within other syntactic approaches.
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