---
# System prepended metadata

title: Meeting with Fede 10/27

---

# Meeting with Fede 10/27

### Agenda

1. Ran sequence classification model (fine-tuned on annotated data) on data and seems to perform really well! Maybe too well?  I've pushed the work to the [linking-lewis clf-19 branch](https://github.com/Living-with-machines/linking-lewis/blob/19-clf/8-TextClassification.ipynb)

2. I also tried running an unsupervised text similarity classification model, but that didn't seem to be able to distinguish matches from mismatches adequately - see [7-TextSimilarityClassification.ipynb](https://github.com/Living-with-machines/linking-lewis/blob/19-clf/7-TextSimilarityClassification.ipynb)
    a. Is this related to issues 10 & 12 in the project board?

3. Data files that would be nice to include for external users:
    a. **lewis.csv**: discussed asking BHO about this with Katie, Daniel, & Ruth - are you okay with providing this (output of lewisprocessing.py) if BHO okays it?
    b. **wikidata_gazetteer.csv**: K, D, & R seemed okay with this if I make a note that this file is what we used but for up-to-date version of Wikidata content, should follow steps in the [toponym-resolution](https://github.com/Living-with-machines/toponym-resolution/tree/dev/preprocessing/wikipediaprocessing) repo - do you agree?
    c. **wikipedia2wikidata.json**: also from [toponym-resolution](https://github.com/Living-with-machines/toponym-resolution/tree/dev/preprocessing/wikipediaprocessing) repo - same as above?
    d. **wikidata_to_mentions.json**: also from [toponym-resolution](https://github.com/Living-with-machines/toponym-resolution/tree/dev/preprocessing/wikipediaprocessing) repo - same as above?
    
**point to https://github.com/fedenanni/Reimplementing-TagMe** 

4.  How to prepare GitHub repo for making public - should I do this?
    a. Including writing the README's Citation, License, & Acknowledgements
    b. Luke recommended creating a config file to store filepath variables
    c. The [lewisprocessing README](https://github.com/Living-with-machines/linking-lewis/tree/dev/lewisprocessing) assumes access to Turing's Azure (the toponymVM)
    d. Keep code in Jupyter Notebooks?
    
5. Have you gotten this error?  I tried updating jupyter but I don't even have ipywidgets... I've gotten a notice that a VS Code update is available, so maybe it's related to that?  (I haven't updated my VS Code yet because I was worried it'd break things)

*Error when I import libraries in the first code cell of a Jupyter Notebook (though libraries all seem to import properly and the error disappears if I run that code cell again)*:
``` 
/home/lhavens/miniconda3/envs/py39/lib/python3.9/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm
```

6. Could try extracting 19th Century text from Wikipedia descriptions and using those for text similarity and sequence classification, compare to introductory text from Wikipedia descriptions and compare to combination of the two

7. How should I prioritize the remaining linking-lewis work we discussed?

8. Exporting *OS-agnostic* environment file:
```
conda env export --from-history > environment.yml
```

  