240 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
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
D-Tree Grammars
DTG are designed to share some of the advantages of TAG while overcoming some
of its limitations. DTG involve two composition operations called subsertion
and sister-adjunction. The most distinctive feature of DTG is that, unlike TAG,
there is complete uniformity in the way that the two DTG operations relate
lexical items: subsertion always corresponds to complementation and
sister-adjunction to modification. Furthermore, DTG, unlike TAG, can provide a
uniform analysis for em wh-movement in English and Kashmiri, despite the fact
that the em wh element in Kashmiri appears in sentence-second position, and not
sentence-initial position as in English.Comment: Latex source, needs aclap.sty, 8 pages, to appear in ACL-9
Constraint Logic Programming for Natural Language Processing
This paper proposes an evaluation of the adequacy of the constraint logic
programming paradigm for natural language processing. Theoretical aspects of
this question have been discussed in several works. We adopt here a pragmatic
point of view and our argumentation relies on concrete solutions. Using actual
contraints (in the CLP sense) is neither easy nor direct. However, CLP can
improve parsing techniques in several aspects such as concision, control,
efficiency or direct representation of linguistic formalism. This discussion is
illustrated by several examples and the presentation of an HPSG parser.Comment: 15 pages, uuencoded and compressed postscript to appear in
Proceedings of the 5th Int. Workshop on Natural Language Understanding and
Logic Programming. Lisbon, Portugal. 199
Hybrid robust deep and shallow semantic processing for creativity support in document production
The research performed in the DeepThought project (http://www.project-deepthought.net) aims at demonstrating the potential of deep linguistic processing if added to existing shallow methods that ensure robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. We use this approach to demonstrate the feasibility of three ambitious applications, one of which is a tool for creativity support in document production and collective brainstorming. This application is described in detail in this paper. Common to all three applications, and the basis for their development is a platform for integrated linguistic processing. This platform is based on a generic software architecture that combines multiple NLP components and on robust minimal recursive semantics (RMRS) as a uniform representation language
BulTreeBank
HPSG-based annotation including: constituent structure, dependency relations, named entities (classified as person, organisation, location or other names), coreferential relations. Annotation in XM
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