Deterministic Parsing using PCFGs

نویسندگان

  • Mark-Jan Nederhof
  • Martin McCaffery
چکیده

We propose the design of deterministic constituent parsers that choose parser actions according to the probabilities of parses of a given probabilistic context-free grammar. Several variants are presented. One of these deterministically constructs a parse structure while postponing commitment to labels. We investigate theoretical time complexities and report experiments.

برای دانلود 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

Non-Local Modeling with a Mixture of PCFGs

While most work on parsing with PCFGs has focused on local correlations between tree configurations, we attempt to model non-local correlations using a finite mixture of PCFGs. A mixture grammar fit with the EM algorithm shows improvement over a single PCFG, both in parsing accuracy and in test data likelihood. We argue that this improvement comes from the learning of specialized grammars that ...

متن کامل

Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs

We describe an approach to speed-up inference with latent-variable PCFGs, which have been shown to be highly effective for natural language parsing. Our approach is based on a tensor formulation recently introduced for spectral estimation of latent-variable PCFGs coupled with a tensor decomposition algorithm well-known in the multilinear algebra literature. We also describe an error bound for t...

متن کامل

A Separate-and-Learn Approach to EM Learning of PCFGs

Wepropose a new approach to EM learning of PCFGs. We completely separate the process of EM learning from that of parsing, and for the former, we introduce a new EM algorithm called the graphical EM algorithm that runs on a new data structure called support graphs extracted from WFSTs (well formed substring tables) of various parsers. Learning experiments with PCFGs using two Japanese corpora in...

متن کامل

Parsing low-resource languages using Gibbs sampling for PCFGs with latent annotations

PCFGs with latent annotations have been shown to be a very effective model for phrase structure parsing. We present a Bayesian model and algorithms based on a Gibbs sampler for parsing with a grammar with latent annotations. For PCFG-LA, we present an additional Gibbs sampler algorithm to learn annotations from training data, which are parse trees with coarse (unannotated) symbols. We show that...

متن کامل

Parsing with PCFGs

The PCFG model is without doubt the most important formal model in syntactic parsing today, not only because it is widely used in itself but also because many later developments start from it. In this lecture, I will first introduce the basic formalism (§1) and the parsing model that naturally follows from it (§2). I will then give an overview of standard techniques for parsing (§3), for superv...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014