A Real-World Data Resource of Complex Sensitive Sentences Based on Documents from the Monsanto Trial

Jan Neerbek, Morten Eskildsen, Peter Dolog, Ira Assent

Abstract
In this work we present a corpus for the evaluation of sensitive information detection approaches that addresses the need for real world sensitive information for empirical studies. Our sentence corpus contains different notions of complex sensitive information that correspond to different aspects of concern in a current trial of the Monsanto company. This paper describes the annotations process, where we both employ human annotators and furthermore create automatically inferred labels regarding technical, legal and informal communication within and with employees of Monsanto, drawing on a classification of documents by lawyers involved in the Monsanto court case. We release corpus of high quality sentences and parse trees with these two types of labels on sentence level. We characterize the sensitive information via several representative sensitive information detection models, in particular both keyword-based (n-gram) approaches and recent deep learning models, namely, recurrent neural networks (LSTM) and recursive neural networks (RecNN). Data and code are made publicly available.
Anthology ID:
2020.lrec-1.158
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1258–1267
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.158
DOI:
Bibkey:
Cite (ACL):
Jan Neerbek, Morten Eskildsen, Peter Dolog, and Ira Assent. 2020. A Real-World Data Resource of Complex Sensitive Sentences Based on Documents from the Monsanto Trial. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1258–1267, Marseille, France. European Language Resources Association.
Cite (Informal):
A Real-World Data Resource of Complex Sensitive Sentences Based on Documents from the Monsanto Trial (Neerbek et al., LREC 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2020.lrec-1.158.pdf
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