4,542 research outputs found
An Efficient Implementation of the Head-Corner Parser
This paper describes an efficient and robust implementation of a
bi-directional, head-driven parser for constraint-based grammars. This parser
is developed for the OVIS system: a Dutch spoken dialogue system in which
information about public transport can be obtained by telephone.
After a review of the motivation for head-driven parsing strategies, and
head-corner parsing in particular, a non-deterministic version of the
head-corner parser is presented. A memoization technique is applied to obtain a
fast parser. A goal-weakening technique is introduced which greatly improves
average case efficiency, both in terms of speed and space requirements.
I argue in favor of such a memoization strategy with goal-weakening in
comparison with ordinary chart-parsers because such a strategy can be applied
selectively and therefore enormously reduces the space requirements of the
parser, while no practical loss in time-efficiency is observed. On the
contrary, experiments are described in which head-corner and left-corner
parsers implemented with selective memoization and goal weakening outperform
`standard' chart parsers. The experiments include the grammar of the OVIS
system and the Alvey NL Tools grammar.
Head-corner parsing is a mix of bottom-up and top-down processing. Certain
approaches towards robust parsing require purely bottom-up processing.
Therefore, it seems that head-corner parsing is unsuitable for such robust
parsing techniques. However, it is shown how underspecification (which arises
very naturally in a logic programming environment) can be used in the
head-corner parser to allow such robust parsing techniques. A particular robust
parsing model is described which is implemented in OVIS.Comment: 31 pages, uses cl.st
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
Apportioning Development Effort in a Probabilistic LR Parsing System through Evaluation
We describe an implemented system for robust domain-independent syntactic
parsing of English, using a unification-based grammar of part-of-speech and
punctuation labels coupled with a probabilistic LR parser. We present
evaluations of the system's performance along several different dimensions;
these enable us to assess the contribution that each individual part is making
to the success of the system as a whole, and thus prioritise the effort to be
devoted to its further enhancement. Currently, the system is able to parse
around 80% of sentences in a substantial corpus of general text containing a
number of distinct genres. On a random sample of 250 such sentences the system
has a mean crossing bracket rate of 0.71 and recall and precision of 83% and
84% respectively when evaluated against manually-disambiguated analyses.Comment: 10 pages, 1 Postscript figure. To Appear in Proceedings of the
Conference on Empirical Methods in Natural Language Processing, University of
Pennsylvania, May 199
Efficient Tabular LR Parsing
We give a new treatment of tabular LR parsing, which is an alternative to
Tomita's generalized LR algorithm. The advantage is twofold. Firstly, our
treatment is conceptually more attractive because it uses simpler concepts,
such as grammar transformations and standard tabulation techniques also know as
chart parsing. Secondly, the static and dynamic complexity of parsing, both in
space and time, is significantly reduced.Comment: 8 pages, uses aclap.st
A Labelled Analytic Theorem Proving Environment for Categorial Grammar
We present a system for the investigation of computational properties of
categorial grammar parsing based on a labelled analytic tableaux theorem
prover. This proof method allows us to take a modular approach, in which the
basic grammar can be kept constant, while a range of categorial calculi can be
captured by assigning different properties to the labelling algebra. The
theorem proving strategy is particularly well suited to the treatment of
categorial grammar, because it allows us to distribute the computational cost
between the algorithm which deals with the grammatical types and the algebraic
checker which constrains the derivation.Comment: 11 pages, LaTeX2e, uses examples.sty and a4wide.st
- …