9,607 research outputs found
A Fuzzy Approach to Erroneous Inputs in Context-Free Language Recognition
Using fuzzy context-free grammars one can easily describe a finite number of ways to derive incorrect strings together with their degree of correctness. However, in general there is an infinite number of ways to perform a certain task wrongly. In this paper we introduce a generalization of fuzzy context-free grammars, the so-called fuzzy context-free -grammars, to model the situation of making a finite choice out of an infinity of possible grammatical errors during each context-free derivation step. Under minor assumptions on the parameter this model happens to be a very general framework to describe correctly as well as erroneously derived sentences by a single generating mechanism.
Our first result characterizes the generating capacity of these fuzzy context-free -grammars. As consequences we obtain: (i) bounds on modeling grammatical errors within the framework of fuzzy context-free grammars, and (ii) the fact that the family of languages generated by fuzzy context-free -grammars shares closure properties very similar to those of the family of ordinary context-free languages.
The second part of the paper is devoted to a few algorithms to recognize fuzzy context-free languages: viz. a variant of a functional version of Cocke-Younger- Kasami's algorithm and some recursive descent algorithms. These algorithms turn out to be robust in some very elementary sense and they can easily be extended to corresponding parsing algorithms
Grammars with two-sided contexts
In a recent paper (M. Barash, A. Okhotin, "Defining contexts in context-free
grammars", LATA 2012), the authors introduced an extension of the context-free
grammars equipped with an operator for referring to the left context of the
substring being defined. This paper proposes a more general model, in which
context specifications may be two-sided, that is, both the left and the right
contexts can be specified by the corresponding operators. The paper gives the
definitions and establishes the basic theory of such grammars, leading to a
normal form and a parsing algorithm working in time O(n^4), where n is the
length of the input string.Comment: In Proceedings AFL 2014, arXiv:1405.527
Towards Robustness in Parsing - Fuzzifying Context-Free Language Recognition
We discuss the concept of robustness with respect to parsing a context-free language. Our approach is based on the notions of fuzzy language, (generalized) fuzzy context-free grammar and parser / recognizer for fuzzy languages. As concrete examples we consider a robust version of Cocke-Younger-Kasami's algorithm and a robust kind of recursive descent recognizer
Parallel on-line parsing in constant time per word
An on-line parser processes each word as soon as it is typed by the user, without waiting for the end of the sentence. Thus, in an interactive system, a sentence will be parsed almost immediately after the last word has been presented.\ud
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The complexity of an on-line parser is determined by the resources needed for the analysis of a single word, as it is assumed that previous words have been processed already. Sequential parsing algorithms like CYK or Earley need O(n2) time for the nth word. A parallel implementation in O(n) time on O(n) processors is straightforward. In this paper a novel parallel on-line parser is presented that needs O(1) time on O(n2) processors
Probabilistic Parsing Strategies
We present new results on the relation between purely symbolic context-free
parsing strategies and their probabilistic counter-parts. Such parsing
strategies are seen as constructions of push-down devices from grammars. We
show that preservation of probability distribution is possible under two
conditions, viz. the correct-prefix property and the property of strong
predictiveness. These results generalize existing results in the literature
that were obtained by considering parsing strategies in isolation. From our
general results we also derive negative results on so-called generalized LR
parsing.Comment: 36 pages, 1 figur
Computation of distances for regular and context-free probabilistic languages
Several mathematical distances between probabilistic languages have been investigated in the literature, motivated by applications in language modeling, computational biology, syntactic pattern matching and machine learning. In most cases, only pairs of probabilistic regular languages were considered. In this paper we extend the previous results to pairs of languages generated by a probabilistic context-free grammar and a probabilistic finite automaton.PostprintPeer reviewe
An Efficient Probabilistic Context-Free Parsing Algorithm that Computes Prefix Probabilities
We describe an extension of Earley's parser for stochastic context-free
grammars that computes the following quantities given a stochastic context-free
grammar and an input string: a) probabilities of successive prefixes being
generated by the grammar; b) probabilities of substrings being generated by the
nonterminals, including the entire string being generated by the grammar; c)
most likely (Viterbi) parse of the string; d) posterior expected number of
applications of each grammar production, as required for reestimating rule
probabilities. (a) and (b) are computed incrementally in a single left-to-right
pass over the input. Our algorithm compares favorably to standard bottom-up
parsing methods for SCFGs in that it works efficiently on sparse grammars by
making use of Earley's top-down control structure. It can process any
context-free rule format without conversion to some normal form, and combines
computations for (a) through (d) in a single algorithm. Finally, the algorithm
has simple extensions for processing partially bracketed inputs, and for
finding partial parses and their likelihoods on ungrammatical inputs.Comment: 45 pages. Slightly shortened version to appear in Computational
Linguistics 2
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
Time-Bounded Controlled Bidirectional Grammars
We study regularly controlled bidirectional (RCB) grammars from the viewpoint of time-bounded grammars. RCB-grammars are context-free grammars of which the rules can be used in a productive and in a reductive fashion, while the application of these rules is controlled by a regular language. Several modes of derivation can be distinguished for this kind of grammar. A time-bound on such a grammar is a measure of its derivational complexity. For some families of time bounds and for some modes of derivation we establish closure properties and a normal form theorem. In addition parsing algorithms are given for some modes of derivation. We conclude with considering generalizations with respect to the family of control languages and the family of bounding functions
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