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Analysis of Automatic Annotation Suggestions for Hard Discourse-Level
  Tasks in Expert Domains

Analysis of Automatic Annotation Suggestions for Hard Discourse-Level Tasks in Expert Domains

6 June 2019
Claudia Schulz
Christian M. Meyer
J. Kiesewetter
Michael Sailer
Elisabeth Bauer
M. Fischer
F. Fischer
Iryna Gurevych
ArXivPDFHTML

Papers citing "Analysis of Automatic Annotation Suggestions for Hard Discourse-Level Tasks in Expert Domains"

3 / 3 papers shown
Title
A Framework for Monitoring and Retraining Language Models in Real-World
  Applications
A Framework for Monitoring and Retraining Language Models in Real-World Applications
Jaykumar Kasundra
Claudia Schulz
Melicaalsadat Mirsafian
Stavroula Skylaki
OffRL
LRM
34
1
0
16 Nov 2023
Consistency is Key: Disentangling Label Variation in Natural Language
  Processing with Intra-Annotator Agreement
Consistency is Key: Disentangling Label Variation in Natural Language Processing with Intra-Annotator Agreement
Gavin Abercrombie
Verena Rieser
Dirk Hovy
54
16
0
25 Jan 2023
Clean or Annotate: How to Spend a Limited Data Collection Budget
Clean or Annotate: How to Spend a Limited Data Collection Budget
Derek Chen
Zhou Yu
Samuel R. Bowman
39
13
0
15 Oct 2021
1