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<Paper uid="P06-1008">
  <Title>Acceptability Prediction by Means of Grammaticality Quantification</Title>
  <Section position="2" start_page="0" end_page="57" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Syntactic formalisms make it possible to describe precisely the question of grammaticality. When a syntactic structure can be associated to a sentence, according to a given grammar, we can decide whether or not the sentence is grammatical.</Paragraph>
    <Paragraph position="1"> In this conception, a language (be it natural or not) isproduced (orgenerated)byagrammarbymeans of a specific mechanism, for example derivation.</Paragraph>
    <Paragraph position="2"> However, when no structure can be built, nothing can be said about the input to be parsed except, eventually, the origin of the failure. This is a problem when dealing with non canonical inputs such as spoken language, e-mails, non-native speaker productions, etc. From this perspective, we need robust approaches that are at the same time capable of describing precisely the form of the input, the source of the problem and to continue the parse. Such capabilities render it possible to arrive at a precise evaluation of the grammaticality of the input. In other words, instead of deciding on the grammaticalityoftheinput, wecangiveanindication of its grammaticality, quantified on the basis of the description of the properties of the input.</Paragraph>
    <Paragraph position="3"> This paper addresses the problem of ranking the grammaticality of different sentences. This question is of central importance for the understanding of language processing, both from an automatic and from a cognitive perspective. As for NLP, ranking grammaticality makes it possible to control dynamically the parsing process (in choosing the most adequate structures) or to find the best structure among a set of solutions (in case of non-deterministic approaches). Likewise the description of cognitive processes involved in language processing by human has to explain how things work when faced with unexpected or non canonical material. In this case too, we have to explain why some productions are more acceptable and easier to process than others.</Paragraph>
    <Paragraph position="4"> The question of ranking grammaticality has been addressed from time to time in linguistics, without being a central concern. Chomsky, for example, mentioned this problem quite regularly (see for example (Chomsky75)). However he rephrases it in terms of &amp;quot;degrees of 'belongingness' to the language&amp;quot;, a somewhat fuzzy notion both formally and linguistically. More recently, several approaches have been proposed illustrating the interest of describing these mechanisms in terms of constraint violations. The idea consists in associating weights to syntactic constraints and to evaluate, either during or after the parse, the weight of violated constraints. This approach is at the basis of Linear Optimality Theory (see (Keller00), and (Sorace05) for a more general perspective) in which grammaticality is judged on the basis of the total weights of violated constraints. It is then possible to rank different candidate struc- null tures. A similar idea is proposed in the framework of Constraint Dependency Grammar (see (Menzel98), (Schr&amp;quot;oder02)). In this case too, acceptability is function of the violated constraints weights. However, constraint violation cannot in itself constitute a measure of grammaticality without taking into account other parameters as well. The type and the number of constraints that are satisfied are of central importance in acceptability judgment: a construction violating 1 constraint and satisfying 15 of them is more acceptable than one violating the same constraint but satisfying only 5 others. In the same way, other informations such as the position of the violation in the structure (whether it occurs in a deeply embedded constituent or higher one in the structure) plays an important role as well.</Paragraph>
    <Paragraph position="5"> In this paper, we propose an approach overcoming such limitations. It takes advantage of a fully constraint-based syntactic formalism (called Property Grammars, cf. (Blache05b)) that offers the possibility of calculating a grammaticality index, taking into account automatically derivedparametersaswellasempiricallydetermined null weights. This index is evaluated automatically and we present a psycholinguistic study showing how the parser predictions converge with acceptability judgments.</Paragraph>
  </Section>
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