def expander_npmi_description()

in utils/gradio_utils.py [0:0]

• 26 lines of code
• 1 McCabe index (conditional complexity)

def expander_npmi_description(min_vocab):
    _NPMI_CAPTION = (
        "Use this widget to identify problematic biases and stereotypes in "
        "your data."
    )
    _NPMI_CAPTION1 = """
    nPMI scores for a word help to identify potentially
    problematic associations, ranked by how close the association is."""
    _NPMI_CAPTION2 = """
    nPMI bias scores for paired words help to identify how word
    associations are skewed between the selected selected words
    ([Aka et al., 2021](https://arxiv.org/abs/2103.03417)).
    """

    st.caption(_NPMI_CAPTION)
    st.markdown(_NPMI_CAPTION1)
    st.markdown(_NPMI_CAPTION2)
    st.markdown("  ")
    st.markdown(
        "You can select from gender and sexual orientation "
        "identity terms that appear in the dataset at least %s "
        "times." % min_vocab
    )
    st.markdown(
        "The resulting ranked words are those that co-occur with both "
        "identity terms.  "
    )
    st.markdown(
        "The more *positive* the score, the more associated the word is with "
        "the first identity term.  "
        "The more *negative* the score, the more associated the word is with "
        "the second identity term."
    )