LR Parsing for LCFRS
نویسندگان
چکیده
LR parsing is a popular parsing strategy for variants of Context-Free Grammar (CFG). It has also been used for mildly context-sensitive formalisms, such as Tree-Adjoining Grammar. In this paper, we present the first LRstyle parsing algorithm for Linear ContextFree Rewriting Systems (LCFRS), a mildly context-sensitive extension of CFG which has received considerable attention in the last years.
منابع مشابه
LCFRS binarization and debinarization for directional parsing
In data-driven parsing with Linear Context-Free Rewriting System (LCFRS), markovized grammars are obtained through the annotation of binarization non-terminals during grammar binarization, as in the corresponding work on PCFG parsing. Since there is indication that directional parsing with a non-binary LCFRS can be faster than parsing with a binary LCFRS, we present a debinarization procedure w...
متن کاملData-Driven Parsing with Probabilistic Linear Context-Free Rewriting Systems
This paper presents a first efficient implementation of a weighted deductive CYK parser for Probabilistic Linear ContextFree Rewriting Systems (PLCFRS), together with context-summary estimates for parse items used to speed up parsing. LCFRS, an extension of CFG, can describe discontinuities both in constituency and dependency structures in a straightforward way and is therefore a natural candid...
متن کاملTreebank Grammar Techniques for Non-Projective Dependency Parsing
An open problem in dependency parsing is the accurate and efficient treatment of non-projective structures. We propose to attack this problem using chart-parsing algorithms developed for mildly contextsensitive grammar formalisms. In this paper, we provide two key tools for this approach. First, we show how to reduce nonprojective dependency parsing to parsing with Linear Context-Free Rewriting...
متن کاملParsing Linear-Context Free Rewriting Systems with Fast Matrix Multiplication
We describe a recognition algorithm for a subset of binary linear context-free rewriting systems (LCFRS) with running time O(nωd) where M(m) = O(m ) is the running time for m×m matrix multiplication and d is the “contact rank” of the LCFRS—the maximal number of combination and non-combination points that appear in the grammar rules. We also show that this algorithm can be used as a subroutine t...
متن کاملData-driven Parsing using PLCFRS Data-driven Parsing using Probabilistic Linear Context-Free Rewriting Systems
This paper presents the first efficient implementation of a weighted deductive CYK parser for Probabilistic Linear Context-Free Rewriting Systems (PLCFRS). LCFRS, an extension of CFG, can describe discontinuities in a straightforward way and is therefore a natural candidate to be used for data-driven parsing. To speed up parsing, we use different context-summary estimates of parse items, some o...
متن کامل