Text2Tag

Code base for the analysis presented in:

• Bowles+2022 "A New Task: Deriving Semantic Class Targets for the Physical Sciences", accepted at NeurIPS 2022, Machine Learning and the Physical Sciences Workshop at the 36th Conference on Neural Information Processing Systems
• Bowles+2023 "Radio galaxy zoo EMU: Towards a semantic radio galaxy morphology taxonomy", Monthly Notices of the Royal Astronomical Society.

The full data used in these works is available on this zenodo including all of the composite cutouts of galaxies presented to citizen scientists.

Quick Start

This repo was built on python 3.8 and a virtual environment. Use the requirements.txt file to install package dependencies into your environment by running:

pip install -r requirements.txt

The SpaCy model requires seperate installation. To install the model used, run

python -m spacy download en_core_web_lg

and / or consult the spaCy documentation for more details.

Re-Running Experiments

With your environment configured, you should be able to run all of our processing. The steps are documented in the (submitted) paper and in the jupyter notebooks.

The main processing steps are implemented in the order presented in main.py.

The utils.py module contains helper functions to summarise and show original annotations which formed a given entry.

Citing

To cite this work (incl. code / data) please cite one or both of the following:

@article{Bowles2023SemanticTags,
    author = {Bowles, Micah and Tang, Hongming and Vardoulaki, Eleni and Alexander, Emma L and Luo, Yan and Rudnick, Lawrence and Walmsley, Mike and Porter, Fiona and Scaife, Anna M M and Slijepcevic, Inigo Val and Adams, Elizabeth A K and Drabent, Alexander and Dugdale, Thomas and Gürkan, Gülay and Hopkins, Andrew M and Jimenez-Andrade, Eric F and Leahy, Denis A and Norris, Ray P and Rahman, Syed Faisal ur and Ouyang, Xichang and Segal, Gary and Shabala, Stanislav S and Wong, O Ivy},
    title = "{Radio galaxy zoo EMU: towards a semantic radio galaxy morphology taxonomy}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {522},
    number = {2},
    pages = {2584-2600},
    year = {2023},
    month = {04},
    issn = {0035-8711},
    doi = {10.1093/mnras/stad1021},
    url = {https://doi.org/10.1093/mnras/stad1021},
    eprint = {https://academic.oup.com/mnras/article-pdf/522/2/2584/50119421/stad1021.pdf},
}

@ARTICLE{Bowles2022_SemanticTags,
       author = {{Bowles}, Micah and {Tang}, Hongming and {Vardoulaki}, Eleni and {Alexander}, Emma L. and {Luo}, Yan and {Rudnick}, Lawrence and {Walmsley}, Mike and {Porter}, Fiona and {Scaife}, Anna M.~M. and {Slijepcevic}, Inigo Val and {Segal}, Gary},
        title = "{A New Task: Deriving Semantic Class Targets for the Physical Sciences}",
      journal = {NeurIPS 2022: Machine Learning and the Physical Sciences Workshop},
     keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Computation and Language},
         year = 2022,
        month = oct,
          eid = {arXiv:2210.14760},
        pages = {arXiv:2210.14760},
archivePrefix = {arXiv},
       eprint = {2210.14760},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv221014760B},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}