Jabberwocky is a toolkit for Natural Language Processing (NLP) and ontologies. Read the documentation for more detail.
| function | description | |
|---|---|---|
| 1. | converter |
convert an excel to an ontology |
| 2. | snatch metadata |
extract metadata from classes |
| 3. | catch text |
annotate corpus with key terms/phrases |
| 4. | rank terms |
rank terms in order of importance |
| 5. | update entities |
update ontology with new classes and metadata |
| 6. | ontology plotting |
plot an ontology via web or tree format |
When combining these Jabberwocky functions, users can create an NLP workflow:
- Within each directory, there is a file
params_*.pywhich users can edit, meaning users shouldn't need to edit the main/primary scripts. - Check the individual directory
READMEsfor parameter information. - Tests are done via the
test/submodule which is theCelestialObjectrepository, here users can see examples of files.
-
Prerequisites - check
requirements.pyfor a list of packages and versions. -
Changelog / Version - see the Changelog (ordered by newest first).
-
Contributing / Issues - please read the Contributing Guidelines also to see past contributors.
-
License - this repo is using the MIT license so users only need to cite if using (see citation below).
@article{Pendleton2020,
doi = {10.21105/joss.02168},
url = {https://doi.org/10.21105/joss.02168},
year = {2020},
publisher = {The Open Journal},
volume = {5},
number = {51},
pages = {2168},
author = {Samantha C. Pendleton and Georgios V. Gkoutos},
title = {Jabberwocky: an ontology-aware toolkit for manipulating text},
journal = {Journal of Open Source Software}
}
- The poem, Jabberwocky, written by Lewis Carrol, is described as a nonsense poem 🐉
- You may think, why not use a Large Language Model (LMM)? Well I wrote a blog to compare w/ LLMs and how they overdo simple tasks, read here.
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