A python package for processing grobid output.
Project description
The grobidmonkey package is an open-source package designed for postprocessing GROBID outputs.
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Documentation: https://github.com/com3dian/Grobidmonkey/tree/master/Document
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Source code: https://github.com/com3dian/Grobidmonkey/tree/master/src/grobidmonkey
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Bug reports: https://github.com/com3dian/Grobidmonkey/issues
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Citing in your work: https://studenttheses.uu.nl/handle/20.500.12932/45939 or
@mastersthesis{lu2024unsupervised,
title={Unsupervised Paper2Slides Generation},
author={Lu, Zehao},
year={2024}
}
grobidmonkey
is a light weight python package built to handle TEI XML files generated by GROBID. It provides a reader class that converts these files into Python dictionaries, making them simple to read and work with. The grobidmonkey reader is capable of reading the entire essay as a dictionary, where each key represents section titles and the corresponding values are lists of section contents in paragraphs. Also the reader provides a method for reading the outline of essay as a tree.
Installation
Currently grobidmonkey is only available in PyPI, and can be installed with
pip install grobidmonkey
Quick Start
from grobidmonkey import reader
monkeyReader = reader.MonkeyReader('monkey') # or 'lxml' or 'x2d'
# read paper outline
outline = monkeyReader.readOutline('/path/to/your/paper.pdf.tei.xml')
# read paper content
essay = monkeyReader.readEssay('/path/to/your/paper.pdf.tei.xml')
For detailed explanantion and tutorial, please check the Document page.
Contirbution
We welcome all contributions, whether they involve code, documentation, or testing, feel free to reach out to me via email at com3dian@outlook.com.
Icon
Gorbidmonkey's icon is a walking monkey.
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About GROBID
GROBID means GeneRation Of BIbliographic Data.
GROBID is a machine learning library for extracting, parsing and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications.
You can also try the GROBID web app with your paper.
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