References¶
How to cite¶
If you want to cite this work, please simply refer to the github project, with optionally the Software Heritage project-level permanent identifier:
grobid-quantities (2015-2022) <https://github.com/kermitt2/grobid-quantities>, swh:1:dir:dbf9ee55889563779a09b16f9c451165ba62b6d7
Here’s a BibTeX entry using the Software Heritage project-level permanent identifier:
@misc{grobid-quantities,
title = {grobid-quantities},
howpublished = {\url{https://github.com/kermitt2/grobid-quantities}},
publisher = {GitHub},
year = {2015--2022},
archivePrefix = {swh},
eprint = {1:dir:dbf9ee55889563779a09b16f9c451165ba62b6d7}
}
Main papers about grobid-quantities¶
Luca Foppiano, Laurent Romary, Masashi Ishii, and Mikiko Tanifuji.
Automatic identification and normalisation of physical measurements in scientific literature.
September 2019, ACM, DocEng ‘19, Berlin, Germany.
Kyle Hundman and Chris A. Mattmann.
Measurement Context Extraction from Text: Discovering Opportunities and Gaps in Earth Science.
2017, KDD 2017, Halifax, Nova Scotia, Canada.
Other¶
UNISCOR (Units Segmentation Corpus) is available at (resources/dataset/units/evaluation/unit-evaluation-corpus.tei.xml).
It was created with the support of NIMS (National Institute for Material Science), in Japan.
For more information, see:
Leveraging Segmentation of Physical Units through a Newly Open Source Corpus.
September 2019, JSAP Fall 2019, Sapporo, Japan