Header

UZH-Logo

Maintenance Infos

A low-complexity, broad-coverage probabilistic Dependency Parser for English


Schneider, G (2003). A low-complexity, broad-coverage probabilistic Dependency Parser for English. In: NAACL/HLT 2003 Student session, Edmonton, Canada, May 2003 - May 2003.

Abstract

Large-scale parsing is still a complex and time-consuming process, often so much that it is in-feasible in real-world applications. The parsing system described here addresses this problem by combining finite-state approaches, statistical parsing techniques and engineering knowl- edge, thus keeping parsing complexity as low as possible at the cost of a slight decrease in performance. The parser is robust and fast and at the same time based on strong linguistic foundations.

Abstract

Large-scale parsing is still a complex and time-consuming process, often so much that it is in-feasible in real-world applications. The parsing system described here addresses this problem by combining finite-state approaches, statistical parsing techniques and engineering knowl- edge, thus keeping parsing complexity as low as possible at the cost of a slight decrease in performance. The parser is robust and fast and at the same time based on strong linguistic foundations.

Statistics

Downloads

72 downloads since deposited on 30 Jul 2009
18 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:May 2003
Deposited On:30 Jul 2009 09:49
Last Modified:15 Aug 2017 05:59

Download

Preview Icon on Download
Preview
Filetype: PDF
Size: 98kB

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations