15,152 research outputs found
Multi-Dimensional Inheritance
In this paper, we present an alternative approach to multiple inheritance for
typed feature structures. In our approach, a feature structure can be
associated with several types coming from different hierarchies (dimensions).
In case of multiple inheritance, a type has supertypes from different
hierarchies. We contrast this approach with approaches based on a single type
hierarchy where a feature structure has only one unique most general type, and
multiple inheritance involves computation of greatest lower bounds in the
hierarchy. The proposed approach supports current linguistic analyses in
constraint-based formalisms like HPSG, inheritance in the lexicon, and
knowledge representation for NLP systems. Finally, we show that
multi-dimensional inheritance hierarchies can be compiled into a Prolog term
representation, which allows to compute the conjunction of two types
efficiently by Prolog term unification.Comment: 9 pages, styles: a4,figfont,eepic,eps
TDL--- A Type Description Language for Constraint-Based Grammars
This paper presents \tdl, a typed feature-based representation language and
inference system. Type definitions in \tdl\ consist of type and feature
constraints over the boolean connectives. \tdl\ supports open- and closed-world
reasoning over types and allows for partitions and incompatible types. Working
with partially as well as with fully expanded types is possible. Efficient
reasoning in \tdl\ is accomplished through specialized modules.Comment: Will Appear in Proc. COLING-9
Representing Isabelle in LF
LF has been designed and successfully used as a meta-logical framework to
represent and reason about object logics. Here we design a representation of
the Isabelle logical framework in LF using the recently introduced module
system for LF. The major novelty of our approach is that we can naturally
represent the advanced Isabelle features of type classes and locales.
Our representation of type classes relies on a feature so far lacking in the
LF module system: morphism variables and abstraction over them. While
conservative over the present system in terms of expressivity, this feature is
needed for a representation of type classes that preserves the modular
structure. Therefore, we also design the necessary extension of the LF module
system.Comment: In Proceedings LFMTP 2010, arXiv:1009.218
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
Comparing Tag Scheme Variations Using an Abstract Machine Generator
In this paper we study, in the context of a WAM-based abstract machine for Prolog, how variations in the encoding of type information in tagged words and in their associated basic operations impact performance and memory usage. We use a high-level language to specify encodings and the associated operations. An automatic generator constructs both the abstract machine using this encoding and the associated Prolog-to-byte code compiler. Annotations in this language make it possible to impose constraints on the final representation of tagged words, such as the effectively addressable space (fixing, for example, the word size of the target processor /architecture), the layout of the tag and value bits inside the tagged word, and how the basic operations are implemented. We evaluate large number of combinations of the different parameters in two scenarios: a) trying to obtain an optimal general-purpose abstract machine and b) automatically generating a specially-tuned abstract machine for a particular program. We conclude that we are able to automatically generate code featuring all the optimizations present in a hand-written, highly-optimized abstract machine and we canal so obtain emulators with larger addressable space and better performance
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