65 research outputs found

    Efficient Parsing for French

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    International audienceParsing with categorial grammars often leads to problems such as proliferating lexical ambiguity, spurious parses and overgeneration. This paper presents a parser for French developed on an unification based categorial grammar (FG) which avoids these problems. This parser is a bottom-up chart parser augmented with a heuristic eliminating spurious parses. The unicity and completeness of parsing are proved

    Report of the EAGLES Workshop on Implemented Formalisms at DFKI, Saarbrücken

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    Report of the EAGLES Workshop on Implemented Formalisms at DFKI, Saarbrücken

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    Principles and Implementation of Deductive Parsing

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    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 definite-clause 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.Comment: 69 pages, includes full Prolog cod

    From UBGs to CFGs A practical corpus-driven approach

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    We present a simple and intuitive unsound corpus-driven approximation method for turning unification-based grammars (UBGs), such as HPSG, CLE, or PATR-II into context-free grammars (CFGs). The method is unsound in that it does not generate a CFG whose language is a true superset of the language accepted by the original unification-based grammar. It is a corpus-driven method in that it relies on a corpus of parsed sentences and generates broader CFGs when given more input samples. Our open approach can be fine-tuned in different directions, allowing us to monotonically come close to the original parse trees by shifting more information into the context-free symbols. The approach has been fully implemented in JAVA. This report updates and extends the paper presented at the International Colloquium on Grammatical Inference (ICGI 2004) and presents further measurements

    High-level methodologies for grammar engineering, introduction to the special issue

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    Lexicalist unification-based machine translation

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    Natural language software registry (second edition)

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    Feature-based inheritance networks for computational lexicons

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    The virtues of viewing the lexicon as an inheritance network are its succinctness and its tendency to highlight significant clusters of linguistic properties. From its succinctness follow two practical advantages, namely its ease of maintenance and modification. In this paper we present a feature-based foundation for lexical inheritance. We argue that the feature-based foundation is both more economical and expressively more powerful than non-feature-based systems. It is more economical because it employs only mechanisms already assumed to be present elsewhere in the grammar (viz., in the feature system), and it is more expressive because feature systems are more expressive than other mechanisms used in expressing lexical inheritance (cf. DATR). The lexicon furthermore allows the use of default unification, based on the ideas of default unification, defined by Bouma. These claims are buttressed in sections sketching the opportunities for lexical description in feature-based lexicons in two central lexical topics, inflection and derivation. Briefly, we argue that the central notion of paradigm may be defined in feature structures, and that it may be more satisfactorily (in fact, immediately) linked to the syntactic information in this fashion. Our discussion of derivation is more programmatic; but here, too, we argue that feature structures of a suitably rich sort provide a foundation for the definition of lexical rules. We illustrate theoretical claims in application to German lexis. This work is currently under implementation in a natural language understanding effort (DISCO) at the German Artiffical Intelligence Center (Deutsches Forschungszentrum für Künstliche Intelligenz)
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