2,501 research outputs found
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
CHR Grammars
A grammar formalism based upon CHR is proposed analogously to the way
Definite Clause Grammars are defined and implemented on top of Prolog. These
grammars execute as robust bottom-up parsers with an inherent treatment of
ambiguity and a high flexibility to model various linguistic phenomena. The
formalism extends previous logic programming based grammars with a form of
context-sensitive rules and the possibility to include extra-grammatical
hypotheses in both head and body of grammar rules. Among the applications are
straightforward implementations of Assumption Grammars and abduction under
integrity constraints for language analysis. CHR grammars appear as a powerful
tool for specification and implementation of language processors and may be
proposed as a new standard for bottom-up grammars in logic programming.
To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200
Principles and Implementation of Deductive Parsing
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
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
Acquiring Word-Meaning Mappings for Natural Language Interfaces
This paper focuses on a system, WOLFIE (WOrd Learning From Interpreted
Examples), that acquires a semantic lexicon from a corpus of sentences paired
with semantic representations. The lexicon learned consists of phrases paired
with meaning representations. WOLFIE is part of an integrated system that
learns to transform sentences into representations such as logical database
queries. Experimental results are presented demonstrating WOLFIE's ability to
learn useful lexicons for a database interface in four different natural
languages. The usefulness of the lexicons learned by WOLFIE are compared to
those acquired by a similar system, with results favorable to WOLFIE. A second
set of experiments demonstrates WOLFIE's ability to scale to larger and more
difficult, albeit artificially generated, corpora. In natural language
acquisition, it is difficult to gather the annotated data needed for supervised
learning; however, unannotated data is fairly plentiful. Active learning
methods attempt to select for annotation and training only the most informative
examples, and therefore are potentially very useful in natural language
applications. However, most results to date for active learning have only
considered standard classification tasks. To reduce annotation effort while
maintaining accuracy, we apply active learning to semantic lexicons. We show
that active learning can significantly reduce the number of annotated examples
required to achieve a given level of performance
Attempto Controlled English (ACE)
Attempto Controlled English (ACE) allows domain specialists to interactively
formulate requirements specifications in domain concepts. ACE can be accurately
and efficiently processed by a computer, but is expressive enough to allow
natural usage. The Attempto system translates specification texts in ACE into
discourse representation structures and optionally into Prolog. Translated
specification texts are incrementally added to a knowledge base. This knowledge
base can be queried in ACE for verification, and it can be executed for
simulation, prototyping and validation of the specification.Comment: 13 pages, compressed, uuencoded Postscript, to be presented at CLAW
96, The First International Workshop on Controlled Language Applications,
Katholieke Universiteit Leuven, 26-27 March 199
Natural Language Processing at the School of Information Studies for Africa
The lack of persons trained in computational linguistic methods is a severe obstacle to making the Internet and computers accessible to people all over the world in their own languages.
The paper discusses the experiences of designing and teaching an introductory course in Natural Language Processing to graduate computer science students at Addis Ababa University, Ethiopia, in order to initiate the education of computational linguists in the Horn of Africa region
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