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PUBLICATIONS

Nestor: A Tool for Natural Language Annotation of Short Texts

Published

Author(s)

Michael Brundage, Rachael Sexton

Abstract

Nestor is a software tool that annotates natural language CSV (comma-separated variable) files, with a UTF-8 encoding, using a process called tagging [1]. The outputted annotated datasets (as either a CSV or .h5 file) can be used for different analysis techniques, such as failure prediction, problem hot spot identification, and maintenance technician expertise assessment, as shown in [2-7]. Currently, the majority of use cases involve maintenance in the engineering domain (manufacturing, mining, heating ventilation and air conditioning (HVAC)), however Nestor can input any natural language CSV file with UTF-8 encoding. The objective is to help analysts make their natural language data, which is often unstructured, filled with technical content, jargon, mispellings, and abbreviations, computable to improve analysis.
Citation
Journal of Research of the National Institute of Standards and Technology
Volume
124
Pub Type
Journals

Download Paper

https://doi.org/10.6028/jres.124.029
Local Download

Keywords

manufacturing, natural language processing, maintenance, software, nestor
Natural language processing, Manufacturing and Information retrieval

Citation

Brundage, M. and Sexton, R. (2019), Nestor: A Tool for Natural Language Annotation of Short Texts, Journal of Research of the National Institute of Standards and Technology, [online], https://doi.org/10.6028/jres.124.029, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928708 (Accessed October 25, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created November 1, 2019, Updated June 12, 2024
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