Higher-order Linear Logic Programming of Categorial Deduction

We show how categorial deduction can be implemented in higher-order (linear) logic programming, thereby realising parsing as deduction for the associative and non-associative Lambek calculi. This provides a method of solution to the parsing problem of Lambek categorial grammar applicable to a variety of its extensions.Comment: 8 pages LaTeX, uses eaclap.sty, to appear EACL9

Automatic F-Structure Annotation from the AP Treebank

We present a method for automatically annotating treebank resources with functional structures. The method defines systematic patterns of correspondence between partial PS configurations and functional structures. These are applied to PS rules extracted from treebanks. The set of techniques which we have developed constitute a methodology for corpus-guided grammar development. Despite the widespread belief that treebank representations are not very useful in grammar development, we show that systematic patterns of c-structure to f-structure correspondence can be simply and successfully stated over such rules. The method is partial in that it requires manual correction of the annotated grammar rules

From treebank resources to LFG F-structures

We present two methods for automatically annotating treebank resources with functional structures. Both methods define systematic patterns of correspondence between partial PS configurations and functional structures. These are applied to PS rules extracted from treebanks, or directly to constraint set encodings of treebank PS trees

Approximate text generation from non-hierarchical representations in a declarative framework

This thesis is on Natural Language Generation. It describes a linguistic realisation system that translates the semantic information encoded in a conceptual graph into an English language sentence. The use of a non-hierarchically structured semantic representation (conceptual graphs) and an approximate matching between semantic structures allows us to investigate a more general version of the sentence generation problem where one is not pre-committed to a choice of the syntactically prominent elements in the initial semantics. We show clearly how the semantic structure is declaratively related to linguistically motivated syntactic representation — we use D-Tree Grammars which stem from work on Tree-Adjoining Grammars. The declarative specification of the mapping between semantics and syntax allows for different processing strategies to be exploited. A number of generation strategies have been considered: a pure topdown strategy and a chart-based generation technique which allows partially successful computations to be reused in other branches of the search space. Having a generator with increased paraphrasing power as a consequence of using non-hierarchical input and approximate matching raises the issue whether certain 'better' paraphrases can be generated before others. We investigate preference-based processing in the context of generation

Design and implementation of an English to Arabic machine translation (MEANA MT).

A new system for Arabic Machine Translation (called MEANA MT) has been built. This system is capable of the analysis of English language as a source and can convert the given sentences into Arabic. The designed system contains three sets of grammar rules governing the PARSING, TRANSFORMATION AND GENERATION PHASES. In the system, word sense ambiguity and some pragmatic patterns were resolved. A new two-way (Analysis/Generation) computational lexicon system dealing with the morphological analysis of the Arabic language has been created. The designed lexicon contains a set of rules governing the morphological inflection and derivation of Arabic nouns, verbs, verb "to be", verb "not to be" and pronouns. The lexicon generates Arabic word forms and their inflectional affixes such as plural and gender morphemes as well as attached pronouns, each according to its rules. It can not parse or generate unacceptable word inflections. This computational system is capable of dealing with vowelized Arabic words by parsing the vowel marks which are attached to the letters. Semantic value pairs were developed to show ~he word sense and other issues in morphology; e.g. genders, numbers and tenses. The system can parse and generate some pragmatic sentences and phrases like proper names, titles, acknowledgements, dates, telephone numbers and addresses. A Lexical Functional Grammar (LFG) formalism is used to combine the syntactic, morphological and semantic features. The grammar rules of this system were implemented and compiled in COMMON. LISP based on Tomita's Generalised LR parsing algorithm, augmented by Pseudo and Full Unification packages. After parsing, sentence constituents of the English sentence are rep- _ resented as Feature Structures (F-Structures). These take part in the transfer and generation process which uses transformation' grammar rules to change the English F-Structure into Arabic F-Structure. These Arabic F-Structure features will be suitable for the Arabic generation grammar to build the required Arabic sentence. This system has been tested on three domains (sentences and phrases); the first is a selected children's story, the second semantic sentences and the third domain consists of pragmatic sentences. This research could be considered as a complete solution for a personal MT system for small messages and sublanguage domains

Proceedings of the Workshop on the lambda-Prolog Programming Language

The expressiveness of logic programs can be greatly increased over first-order Horn clauses through a stronger emphasis on logical connectives and by admitting various forms of higher-order quantification. The logic of hereditary Harrop formulas and the notion of uniform proof have been developed to provide a foundation for more expressive logic programming languages. The λ-Prolog language is actively being developed on top of these foundational considerations. The rich logical foundations of λ-Prolog provides it with declarative approaches to modular programming, hypothetical reasoning, higher-order programming, polymorphic typing, and meta-programming. These aspects of λ-Prolog have made it valuable as a higher-level language for the specification and implementation of programs in numerous areas, including natural language, automated reasoning, program transformation, and databases