Integration Of Syntactic And Lexical Information In A Hierarchical Dependency Grammar

In this paper, we propose to introduce syntactic classes in a lexicalized dependency formalism. Subcategories of words are organized hierarchically from a general, abstract level (syntactic categories) to a word-specific level (single lexical items). The formalism is parsimonious, and useful for processing. We also sketch a parsing model that uses the hierarchical mixed-grain representation to make predictions on the structure of the input. 1 I n t r o d u c t i o n Much recent work in linguistics and computational linguistics emphasizes the role of lexical information in syntactic representation and processing. This emphasis given to the lexicon is the result of a gradual process. The original trend in linguistics has been to individuate categories of words having related characteristics the traditional syntactic categories like verb, noun, adjective, etc. and to express the structure of a sentence in terms of constituents, or phrases, built around these categories. Subsequent considerations lead to a lexicalization of grammar. Linguistically, the constraints expressed on syntactic categories are too general to explain facts about words e.g. the relation between a verb and its nominalization, "destroy the city" and "destruction of the city" or to account uniformly for a number of phenomena across languages e.g. passivization. In parsing, the use of individual item information reduces the search space of the possible structures of a sentence. From a mathematical point of view, lexicalized grammars exhibit properties like finite ambiguity (Schabes, 1990) that are of a practical interest (especially in writing realistic grammars). Dependency grammar is naturally suitable for a lexicalization, as the binary relations representing the structure of a sentence are defined with respect to the head (that is a word). Pure lexicalized formalisms, however, have also several disadvantages. Linguistically, the abstract level provided by syntactic rules is necessary to avoid the loss of generalization which would arise if classlevel information were repeated in all lexical items. In parsing, a predictive component is required to guarantee the valid prefiz property, namely the capabifity of detecting as soon as possible whether a substring is a valid prefix for the language defined by the grammar. Knowledge of syntactic categories, which does not depend on the input, is needed for a parser to be predictive. In this paper we address the problem of the interaction between syntactic and lexical information in dependency grammar. We introduce many intermediate levels between lexical items and syntactic categories, by organizing the grammar around the notion of subcategorizetion. Intuitively, a subcategorization frame for a lexical item L is a specification of the number and type of elements that L requires in order, for ml utterance that contains L, to be well-formed. For example, within the syntactic category VERB, different verbs require different numbers of nominal dependents for a well-formed sentence. In Italian (our case study), an intransitive verb such as dormirv, "sleep", subcategorizes for only one nominal element (the subject), while a transitive verb such as baciare, "kiss", subcategorizes for two nominal elements (the subject and the object) 1. Grammatical relations such as subject and object are primitive concepts in a dependency paradigm, i.e. they directly define the structure of the sentence. Consequently, the dependency paradigm is particularly suitable to define the grammar in terms of constraints on subcategorization frames. Our proposal is to use subcategories organized in a hierarchy: the upper level of the hierarchy corresponds to the syntactic categories, the other levels correspond to subcategories that are more and more 1We include the subject relation in the subcategorization, or valency, of a verb cf. (Hudson, 1990) (Mel'cuk, 1988). In most constituency theories, on the contrary, the subject is not part of the valency of a verb.