A Legal Perspective on Training Models for Natural Language Processing

被引：0
|
作者：
de Castilho, Richard Eckart [1 ]
Dore, Giulia [2 ]
Margoni, Thomas [2 ]
Labropoulou, Penny [3 ]
Gurevych, Iryna [1 ]
机构：
[1] Tech Univ Darmstadt, Dept Comp Sci, UKP Lab, Darmstadt, Germany
[2] Univ Glasgow, Sch Law, CREATe Ctr, Glasgow, Lanark, Scotland
[3] Athena RC, Inst Language & Speech Proc, Maroussi, Greece
来源：
PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2018) | 2018年
基金：
欧盟地平线“2020”;
关键词：
Copyright; Licensing; Machine Learning; Annotated Corpora;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A significant concern in processing natural language data is the often unclear legal status of the input and output data/resources. In this paper, we investigate this problem by discussing a typical activity in Natural Language Processing: the training of a machine learning model from an annotated corpus. We examine which legal rules apply at relevant steps and how they affect the legal status of the results, especially in terms of copyright and copyright-related rights.
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页码：1267 / 1274
页数：8
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