Abstract
Collection of tools designed to parse documents, such as PDFs, and extract structured elements including URLs, citation contexts, tables, formulas, and figures. This toolset leverages AI-based text extraction and classification methods, providing robust solutions for various scholarly resources processing needs.
- Developers:
- Release Date:
- 2024-09-10
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Licenses:
-
MIT License
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC52-06NA25396
- Code ID:
- 148730
- Site Accession Number:
- O4805
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Country of Origin:
- United States
Citation Formats
Balakireva, Lyudmila, and Johnson, Dylan.
Library-AI-Toolset.
Computer Software.
https://github.com/lanl/Library-AI-Toolset.
USDOE.
10 Sep. 2024.
Web.
doi:10.11578/dc.20241213.2.
Balakireva, Lyudmila, & Johnson, Dylan.
(2024, September 10).
Library-AI-Toolset.
[Computer software].
https://github.com/lanl/Library-AI-Toolset.
https://doi.org/10.11578/dc.20241213.2.
Balakireva, Lyudmila, and Johnson, Dylan.
"Library-AI-Toolset." Computer software.
September 10, 2024.
https://github.com/lanl/Library-AI-Toolset.
https://doi.org/10.11578/dc.20241213.2.
@misc{
doecode_148730,
title = {Library-AI-Toolset},
author = {Balakireva, Lyudmila and Johnson, Dylan},
abstractNote = {Collection of tools designed to parse documents, such as PDFs, and extract structured elements including URLs, citation contexts, tables, formulas, and figures. This toolset leverages AI-based text extraction and classification methods, providing robust solutions for various scholarly resources processing needs.},
doi = {10.11578/dc.20241213.2},
url = {https://doi.org/10.11578/dc.20241213.2},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20241213.2}},
year = {2024},
month = {sep}
}