Integrating World Knowledge with Cognitive Parsing

The work presented in this article builds on the account of cognitive parsing given by the SOUL system (Konieczny & Strube, 1995), an object-oriented implementation of Parameterized Head Attachment (Konieczny et al, 1991) based on Head-Driven Phrase-Structure Grammar (Pollard & Sag, 1994). We describe how the initial semantic representation proposed by the parser is translated into a logical form suitable for inference, thus making it possible to integrate world knowledge with cognitive parsing. As a semantic and knowledge representation system we use the most expressive implemented logic for natural language understanding. Episodic Logic (Hwang & Schubert, 1993), and its computational implementation, Epilog (Schaeffer et al, 1991)

A Sign-Based Phrase Structure Grammar for Turkish

This study analyses Turkish syntax from an informational point of view. Sign based linguistic representation and principles of HPSG (Head-driven Phrase Structure Grammar) theory are adapted to Turkish. The basic informational elements are nested and inherently sorted feature structures called signs. In the implementation, logic programming tool ALE (Attribute Logic Engine) which is primarily designed for implementing HPSG grammars is used. A type and structure hierarchy of Turkish language is designed. Syntactic phenomena such a s subcategorization, relative clauses, constituent order variation, adjuncts, nomina l predicates and complement-modifier relations in Turkish are analyzed. A parser is designed and implemented in ALE.Comment: MS. Thesis, Dept. of Computer Engineering, Middle East Technical University, Ankara January, 1996, 97 pages. 5 eps figures, uses avm,psfig,lingmacros,tree-dvips,ulem,QobiTree,alltt ulem.sty,QobiTree.sty,alltt.sty and eps files included in ta

Amalia -- A Unified Platform for Parsing and Generation

Contemporary linguistic theories (in particular, HPSG) are declarative in nature: they specify constraints on permissible structures, not how such structures are to be computed. Grammars designed under such theories are, therefore, suitable for both parsing and generation. However, practical implementations of such theories don't usually support bidirectional processing of grammars. We present a grammar development system that includes a compiler of grammars (for parsing and generation) to abstract machine instructions, and an interpreter for the abstract machine language. The generation compiler inverts input grammars (designed for parsing) to a form more suitable for generation. The compiled grammars are then executed by the interpreter using one control strategy, regardless of whether the grammar is the original or the inverted version. We thus obtain a unified, efficient platform for developing reversible grammars.Comment: 8 pages postscrip

An Abstract Machine for Unification Grammars

This work describes the design and implementation of an abstract machine, Amalia, for the linguistic formalism ALE, which is based on typed feature structures. This formalism is one of the most widely accepted in computational linguistics and has been used for designing grammars in various linguistic theories, most notably HPSG. Amalia is composed of data structures and a set of instructions, augmented by a compiler from the grammatical formalism to the abstract instructions, and a (portable) interpreter of the abstract instructions. The effect of each instruction is defined using a low-level language that can be executed on ordinary hardware. The advantages of the abstract machine approach are twofold. From a theoretical point of view, the abstract machine gives a well-defined operational semantics to the grammatical formalism. This ensures that grammars specified using our system are endowed with well defined meaning. It enables, for example, to formally verify the correctness of a compiler for HPSG, given an independent definition. From a practical point of view, Amalia is the first system that employs a direct compilation scheme for unification grammars that are based on typed feature structures. The use of amalia results in a much improved performance over existing systems. In order to test the machine on a realistic application, we have developed a small-scale, HPSG-based grammar for a fragment of the Hebrew language, using Amalia as the development platform. This is the first application of HPSG to a Semitic language.Comment: Doctoral Thesis, 96 pages, many postscript figures, uses pstricks, pst-node, psfig, fullname and a macros fil

Robust Grammatical Analysis for Spoken Dialogue Systems

We argue that grammatical analysis is a viable alternative to concept spotting for processing spoken input in a practical spoken dialogue system. We discuss the structure of the grammar, and a model for robust parsing which combines linguistic sources of information and statistical sources of information. We discuss test results suggesting that grammatical processing allows fast and accurate processing of spoken input.Comment: Accepted for JNL