MACE-AL

A method for detecting noise in automatically annotated sequence-labelled data, combining MACE (Hovy et al. 2013) with Active Learning.

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Bibliographic Details
Main Authors: Rehbein, Ines (Author) , Ruppenhofer, Josef (Author) , Steen, Julius (Author)
Format: Database Research Data
Language:English
Published: Heidelberg Universität 2020-03-26
DOI:10.11588/data/C2OQN4
Subjects:
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.11588/data/C2OQN4
Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/C2OQN4
Verlag, kostenfrei, Volltext: https://github.com/julmaxi/MACE-AL
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Author Notes:Ines Rehbein, Josef Ruppenhofer, Julius Steen
Description
Summary:A method for detecting noise in automatically annotated sequence-labelled data, combining MACE (Hovy et al. 2013) with Active Learning.
Item Description:Production date: 2017
Kind of data: Python code
Gesehen am 31.03.2020
Physical Description:Online Resource
DOI:10.11588/data/C2OQN4