We present a system for generating parsers based directly on the metaphor of parsing as deduction. Parsing algorithms can be represented directly as deduction systems, and a single deduction engine can interpret such deduction systems so as to implement the corresponding parser. The method generalizes easily to parsers for augmented phrase structure formalisms, such as definiteclause grammars and other logic grammar formalisms, and has been used for rapid prototyping of parsing algorithms for a variety of formalisms including variants of tree-adjoining grammars, categorial grammars, and lexicalized context-free grammars.

Several real-world problems call for more parsing power than is offered by the widely used and well-established deterministic parsing techniques. These techniques also create an artificial divide between lexical and context-free analysis phases, at the cost of significant complexity at their interface. In this paper we present the fusion of generalized LR parsing and scannerless parsing. This combination supports syntax definitions in which all aspects (lexical and context-free) of the syntax of a language are defined explicitly in one formalism. Furthermore, there are no restrictions on the class of grammars, thus allowing a natural syntax tree structure. Ambiguities that arise through the use of unrestricted grammars are handled by explicit disambiguation constructs, instead of implicit defaults that are taken by traditional scanner and parser generators. Hence, a syntax definition becomes a full declarative description of a language. Disambiguation constructs can be interpreted as filters on parse forests. Depending on the kind of disambiguation, filters can be applied at parser generation time, at parse time, or after parsing. Scannerless generalized LR parsing is a viable technique that has been applied in various industrial and academic projects.

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We evaluate the parsing technology used by people working in the reengineering industry. We discuss parser generators and complete systems like Yacc, TXL, TAMPR, REFINE, CobolTransformer, COSMOS, and ASF+SDF. We explain the merits and drawbacks of the various techniques. We conclude that current technology may cause problems for the reengineering industry and that modular and/or compositional parsing techniques are a possible solution. Categories and Subject Description: D.2.6 [Software Engineering ]: Programming Environments---Interactive; D.2.7 [Software Engineering]: Distribution and Maintenance--- Restructuring; D.3.4. [Processors]: Parsing. Additional Key Words and Phrases: Reengineering, System renovation, Parsing, Generalized LR parsing, compositional grammars, modular grammars. 1 Introduction A hardly controversial statement in the reengineering community is that in order to reengineer software it is convenient to parse it. Maybe due to the overall agreement on this issue, ...

The thesis describes novel techniques and algorithms for the practical parsing of realistic Natural Language (NL) texts with a wide-coverage unification-based grammar of English. The thesis tackles two of the major problems in this area: firstly, the fact that parsing realistic inputs with such grammars can be computationally very expensive, and secondly, the observation that many analyses are often assigned to an input, only one of which usually forms the basis of the correct interpretation. The thesis starts by presenting a new unification algorithm, justifies why it is well-suited to practical NL parsing, and describes a bottom-up active chart parser which employs this unification algorithm together with several other novel processing and optimisation techniques. Empirical results demonstrate that an implementation of this parser has significantly better practical

Introduction Many of the formalisms used to define the syntax of natural (and programming) languages may be located in a continuum that ranges from propositional Horn logic to full first order Horn logic, possibly with non-Herbrand interpretations. This structural parenthood has been previously remarked: it lead to the development of Prolog [Col-78, Coh-88] and is analyzed in some detail in [PerW-80] for Context-Free languages and Horn Clauses. A notable outcome is the parsing technique known as Earley deduction [PerW-83]. These formalisms play (at least) three roles: descriptive: they give a finite and organized description of the syntactic structure of the language, analytic: they can be used to analyze sentences so as to retrieve a syntactic structure (i.e. a representation) from which the meaning can be extracted, generative: they can also be used as the specification of the concrete representation of sentences from a more

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Best-first probabilistic chart parsing attempts to parse efficiently by working on edges that are judged 'best' by some probabilistic figure of merit (FOM). Recent work has used proba- bilistic context-free grammars (PCFGs) to sign probabilities to constituents, and to use these probabilities as the starting point for the FOM. This paper extends this approach to us- ing a probabilistic FOM to judge edges (incomplete constituents), thereby giving a much finergrained control over parsing effort. We show how this can be accomplished in a particularly simple way using the common idea of binarizing the PCFG. The results obtained are about a factor of twenty improvement over the best prior results -- that is, our parser achieves equivalent results using one twentieth the number of edges. Furthermore we show that this improvement is obtained with parsing precision and recall levels superior to those achieved by exhaustive parsing.

this paper is to discuss the scope and limitations of this approach, and to examine the suitability of several syntactic formalisms on the criterion of their ability to handle it. 2 Parsing as intersection

The paper demonstrates that exponential complexities with respect to grammar size and input length have little impact on the performance of three unification-based parsing algorithms, using a wide-coverage grammar. The results imply that tile study and optimisation of unification-based parsing must rely on empirical data until complexity theory can more accurately predict the practical behaviour of such parsers.