Time Reduction of Stochastic Parsing with Stochastic Context-Free Grammars

نویسندگان

  • Joan-Andreu Sánchez
  • José-Miguel Benedí
چکیده

This paper proposes an approach to reduce the stochastic parsing time with stochastic context-free grammars. The basic idea consists of storing a set of precomputed problems. These precomputed problems are obtained off line from a training corpus or they are computed on line from a test corpus. In this work, experiments with the UPenn Treebank are reported in order to show the performance of both alternatives.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Parsing with the Shortest Derivation

Common wisdom has it that the bias of stochastic grammars in favor of shorter derivations of a sentence is harmful and should be redressed. We show that the common wisdom is wrong for stochastic grammars that use elementary trees instead of context-free rules, such as Stochastic Tree-Substitution Grammars used by Data-Oriented Parsing models. For such grammars a non-probabilistic metric based o...

متن کامل

Parsing Strategies for the Integration of Two Stochastic Context-free Grammars

Integration of two stochastic context-free grammars can be useful in two pass approaches used, for example, in speech recognition and understanding. Based on an algorithm proposed by [Nederhof and Satta, 2002] for the non-probabilistic case, left-to-right strategies for the search for the best solution based on CKY and Earley parsers are discussed. The restriction that one of the two grammars m...

متن کامل

Synchronous Context-Free Grammars and Optimal Linear Parsing Strategies

Synchronous Context-Free Grammars (SCFGs), also known as syntax-directed translation schemata [AU69, AU72], 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 pars...

متن کامل

Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars

We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, beta-sheet regions in particular, using a class of stochastic tree grammars as representational language for their amino acid sequence patterns. The family of stochastic tree grammars we use, the Stochastic Ranked Node Rewriting Grammars (SRNRG), is one of the rare families of stochastic gramma...

متن کامل

Iterative CKY Parsing for Probabilistic Context-Free Grammars

This paper presents an iterative CKY parsing algorithm for probabilistic contextfree grammars (PCFG). This algorithm enables us to prune unnecessary edges produced during parsing, which results in more efficient parsing. Since pruning is done by using the edge’s inside Viterbi probability and the upper-bound of the outside Viterbi probability, this algorithm guarantees to output the exact Viter...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005