1,612 research outputs found
Attempto - From Specifications in Controlled Natural Language towards Executable Specifications
Deriving formal specifications from informal requirements is difficult since
one has to take into account the disparate conceptual worlds of the application
domain and of software development. To bridge the conceptual gap we propose
controlled natural language as a textual view on formal specifications in
logic. The specification language Attempto Controlled English (ACE) is a subset
of natural language that can be accurately and efficiently processed by a
computer, but is expressive enough to allow natural usage. The Attempto system
translates specifications in ACE into discourse representation structures and
into Prolog. The resulting knowledge base can be queried in ACE for
verification, and it can be executed for simulation, prototyping and validation
of the specification.Comment: 15 pages, compressed, uuencoded Postscript, to be presented at EMISA
Workshop 'Naturlichsprachlicher Entwurf von Informationssystemen -
Grundlagen, Methoden, Werkzeuge, Anwendungen', May 28-30, 1996, Ev. Akademie
Tutzin
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
Learning morphological phenomena of Modern Greek an exploratory approach
This paper presents a computational model for the description of concatenative morphological phenomena of modern Greek (such as inflection, derivation and compounding) to allow learners, trainers and developers to explore linguistic processes through their own constructions in an interactive openāended multimedia environment. The proposed model introduces a new language metaphor, the āpuzzleāmetaphorā (similar to the existing āturtleāmetaphorā for concepts from mathematics and physics), based on a visualized unificationālike mechanism for pattern matching. The computational implementation of the model can be used for creating environments for learning through design and learning by teaching
The ModelCC Model-Driven Parser Generator
Syntax-directed translation tools require the specification of a language by
means of a formal grammar. This grammar must conform to the specific
requirements of the parser generator to be used. This grammar is then annotated
with semantic actions for the resulting system to perform its desired function.
In this paper, we introduce ModelCC, a model-based parser generator that
decouples language specification from language processing, avoiding some of the
problems caused by grammar-driven parser generators. ModelCC receives a
conceptual model as input, along with constraints that annotate it. It is then
able to create a parser for the desired textual syntax and the generated parser
fully automates the instantiation of the language conceptual model. ModelCC
also includes a reference resolution mechanism so that ModelCC is able to
instantiate abstract syntax graphs, rather than mere abstract syntax trees.Comment: In Proceedings PROLE 2014, arXiv:1501.0169
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