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Extending Bidirectional Chart Parsing with a Stochastic Model

Summary: Extending Bidirectional Chart Parsing with a
Stochastic Model
Alicia Ageno and Horacio Rodríguez
LSI Department. Universidad Politècnica de Catalunya (UPC)
Jordi Girona, 1-3. E-08034 Barcelona, Spain
{ageno, horacio}@lsi.upc.es
Abstract. A method for stochastically modeling bidirectionality in chart
parsing is presented. A bidirectional parser, which starts analysis from certain
dynamically determined positions of the sentence (the islands), has been built.
This island-driven parser uses the stochastic model to guide the recognition
process. The system has been trained and tested over two wide-coverage
corpus: Spanish Lexesp and English Penn Treebank. Results regarding
comparison of our approach with the basic Bottom-Up are encouraging.
1 Introduction
Although most methods for CFG parsing are based on a uniform way of guiding the
parsing process (e.g. top-down, bottom-up, left-corner,...), there have recently been
several attempts to introduce more flexibility, for instance allowing bidirectionality,
in order to make parsers more sensitive to linguistic phenomena (see [1], [2], [3]).
We can roughly classify such approaches into head-driven and island-driven
parsing. They respectively assume the existence of a distinguished symbol in each


Source: Ageno, Alicia - Departament of Llenguatges i Sistemes Informátics, Universitat Politècnica de Catalunya


Collections: Computer Technologies and Information Sciences