Volltext-Downloads (blau) und Frontdoor-Views (grau)
The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 90 of 10097
Back to Result List

Sprucing up the trees – error detection in treebanks

  • We present a method for detecting annotation errors in manually and automatically annotated dependency parse trees, based on ensemble parsing in combination with Bayesian inference, guided by active learning. We evaluate our method in different scenarios: (i) for error detection in dependency treebanks and (ii) for improving parsing accuracy on in- and out-of-domain data.

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Author:Ines Rehbein, Josef Ruppenhofer
URN:urn:nbn:de:bsz:mh39-79938
URL:http://aclweb.org/anthology/C18-1010
ISBN:978-1-948087-50-6
Parent Title (English):Proceedings of the 27th International Conference on Computational Linguistics. August 20-26, 2018 Santa Fe, New Mexico, USA (COLING 2018)
Publisher:The Association for Computational Linguistics
Place of publication:Stroudsburg PA, USA
Editor:Emily M. Bender, Leon Derczynski, Pierre Isabelle
Document Type:Part of a Book
Language:English
Year of first Publication:2018
Date of Publication (online):2018/09/26
Publicationstate:Veröffentlichungsversion
Reviewstate:Peer-Review
GND Keyword:Annotation; Automatische Spracherkennung; Parser
First Page:107
Last Page:118
DDC classes:400 Sprache / 400 Sprache, Linguistik
Open Access?:ja
Leibniz-Classification:Sprache, Linguistik
Program areas:Pragmatik
Program areas:Digitale Sprachwissenschaft
Licence (English):License LogoCreative Commons - Attribution 4.0 International