Grammar Learning by Partition Search

نویسنده

  • Anja Belz
چکیده

This paper describes Grammar Learning by Partition Search, a general method for automatically constructing grammars for a range of parsing tasks. Given a base grammar, a training corpus, and a parsing task, Partition Search constructs an optimised probabilistic context-free grammar by searching a space of nonterminal set partitions, looking for a partition that maximises parsing performance and minimises grammar size. The method can be used to optimise grammars in terms of size and performance, or to adapt existing grammars to new parsing tasks and new domains. This paper reports an example application to optimising a base grammar extracted from the Wall Street Journal Corpus. Partition Search improves parsing performance by up to 5.29%, and reduces grammar size by up to 16.89%. Parsing results are better than in existing treebank grammar research, and compared to other grammar compression methods, Partition Search has the advantage of achieving compression without loss of grammar coverage.

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

Learning Grammars for Noun Phrase Extraction by Partition Search

This paper describes an application of Grammar Learning by Partition Search to noun phrase extraction, an essential task in information extraction and many other NLP applications. Grammar Learning by Partition Search is a general method for automatically constructing grammars for a range of parsing tasks; it constructs an optimised probabilistic context-free grammar by searching a space of nont...

متن کامل

ITRI-02-14 Learning Grammars for Noun Phrase Extraction by Partition Search

This paper describes an application of Grammar Learning by Partition Search to noun phrase extraction, an essential task in information extraction and many other NLP applications. Grammar Learning by Partition Search is a general method for automatically constructing grammars for a range of parsing tasks; it constructs an optimised probabilistic context-free grammar by searching a space of nont...

متن کامل

ITRI-02-09 Grammar Learning by Partition Search

This paper describes Grammar Learning by Partition Search, a general method for automatically constructing grammars for a range of parsing tasks. Given a base grammar, a training corpus, and a parsing task, Partition Search constructs an optimised probabilistic context-free grammar by searching a space of nonterminal set partitions, looking for a partition that maximises parsing performance and...

متن کامل

ITRI-02-16 PCFG Learning by Nonterminal Partition Search

pcfg Learning by Partition Search is a general grammatical inference method for constructing, adapting and optimising pcfgs. Given a training corpus of examples from a language, a canonical grammar for the training corpus, and a parsing task, Partition Search pcfg Learning constructs a grammar that maximises performance on the parsing task and minimises grammar size. This paper describes Partit...

متن کامل

PCFG Learning by Nonterminal Partition Search

pcfg Learning by Partition Search is a general grammatical inference method for constructing, adapting and optimising pcfgs. Given a training corpus of examples from a language, a canonical grammar for the training corpus, and a parsing task, Partition Search pcfg Learning constructs a grammar that maximises performance on the parsing task and minimises grammar size. This paper describes Partit...

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 2002