Back to Search Start Over

AI Approaches to Statistical Language Models

Authors :
BROWN UNIV PROVIDENCE RI DEPT OF COMPUTER SCIENCE
Charniak, Eugene
BROWN UNIV PROVIDENCE RI DEPT OF COMPUTER SCIENCE
Charniak, Eugene
Source :
DTIC AND NTIS
Publication Year :
2000

Abstract

We have made a number of advances under this grant. We have created what is currently the most accurate parser for parsing into Penn-tree-bank-style trees; a program that identifies the antecedents of pronouns with 85% accuracy; a program that assigns function tags to parse text with 85% accuracy; a program that assigns referents to full noun phrases with 65% accuracy; very efficient parsers that explore very few constituents that do not appear in the final parse; and programs that discover semantic information about words from unlabeled text. Furthermore, all these programs work by statistical means.

Details

Database :
OAIster
Journal :
DTIC AND NTIS
Notes :
text/html, English
Publication Type :
Electronic Resource
Accession number :
edsoai.ocn831695405
Document Type :
Electronic Resource