3,244 research outputs found
Synchronous Context-Free Grammars and Optimal Linear Parsing Strategies
Synchronous Context-Free Grammars (SCFGs), also known as syntax-directed
translation schemata, are unlike context-free grammars in that they do not have
a binary normal form. In general, parsing with SCFGs takes space and time
polynomial in the length of the input strings, but with the degree of the
polynomial depending on the permutations of the SCFG rules. We consider linear
parsing strategies, which add one nonterminal at a time. We show that for a
given input permutation, the problems of finding the linear parsing strategy
with the minimum space and time complexity are both NP-hard
An Alternative Conception of Tree-Adjoining Derivation
The precise formulation of derivation for tree-adjoining grammars has
important ramifications for a wide variety of uses of the formalism, from
syntactic analysis to semantic interpretation and statistical language
modeling. We argue that the definition of tree-adjoining derivation must be
reformulated in order to manifest the proper linguistic dependencies in
derivations. The particular proposal is both precisely characterizable through
a definition of TAG derivations as equivalence classes of ordered derivation
trees, and computationally operational, by virtue of a compilation to linear
indexed grammars together with an efficient algorithm for recognition and
parsing according to the compiled grammar.Comment: 33 page
Hairdressing in groups: a survey of combings and formal languages
A group is combable if it can be represented by a language of words
satisfying a fellow traveller property; an automatic group has a synchronous
combing which is a regular language. This article surveys results for combable
groups, in particular in the case where the combing is a formal language.Comment: 17 pages. Published copy, also available at
http://www.maths.warwick.ac.uk/gt/GTMon1/paper24.abs.htm
A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena
Word reordering is one of the most difficult aspects of statistical machine
translation (SMT), and an important factor of its quality and efficiency.
Despite the vast amount of research published to date, the interest of the
community in this problem has not decreased, and no single method appears to be
strongly dominant across language pairs. Instead, the choice of the optimal
approach for a new translation task still seems to be mostly driven by
empirical trials. To orientate the reader in this vast and complex research
area, we present a comprehensive survey of word reordering viewed as a
statistical modeling challenge and as a natural language phenomenon. The survey
describes in detail how word reordering is modeled within different
string-based and tree-based SMT frameworks and as a stand-alone task, including
systematic overviews of the literature in advanced reordering modeling. We then
question why some approaches are more successful than others in different
language pairs. We argue that, besides measuring the amount of reordering, it
is important to understand which kinds of reordering occur in a given language
pair. To this end, we conduct a qualitative analysis of word reordering
phenomena in a diverse sample of language pairs, based on a large collection of
linguistic knowledge. Empirical results in the SMT literature are shown to
support the hypothesis that a few linguistic facts can be very useful to
anticipate the reordering characteristics of a language pair and to select the
SMT framework that best suits them.Comment: 44 pages, to appear in Computational Linguistic
Precise n-gram Probabilities from Stochastic Context-free Grammars
We present an algorithm for computing n-gram probabilities from stochastic
context-free grammars, a procedure that can alleviate some of the standard
problems associated with n-grams (estimation from sparse data, lack of
linguistic structure, among others). The method operates via the computation of
substring expectations, which in turn is accomplished by solving systems of
linear equations derived from the grammar. We discuss efficient implementation
of the algorithm and report our practical experience with it.Comment: 12 pages, to appear in ACL-9
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