Skip to content

Instantly share code, notes, and snippets.

What would you like to do?
This gist is part of my blogpost on BERT. Find the complete blogpost, covering both theory and hands-on part, here:
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Copy link

For some reason when saving that alpha (a) saves as first column and was messing up the training.
I changed that "alpha" column to "poop" and it fixed it. (think it is just saving columns alphabetically, maybe there is better fix here haha)

df_bert = pd.DataFrame({
'text': train_df[1].replace(r'\n', ' ', regex=True)

Copy link

Hey sir, can you tell me, how can I map words, only nouns, and adjectives to particular classes and properties of the Graph database, DO I have to create a dataset for each word and their respective classes and properties in an Ontology?

I am working on Q&A System for the graph database basically , I found research paper that do these thing but I don't think of how to achieve this.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment