First of all, thanks for creating scispacy, I think it's an amazing tool and very useful!!

I was running into an issue when saving the output of scispacy. I tried to pickle a Doc object, as explained on the website of spaCy, as follows:

import spacy
import pickle

nlp = spacy.load("en_core_sci_sm")

# add the Abbreviation Detector
abbrev

Please replace every line in curly brackets { like this } with an appropriate description, and remove this line.

Description

{ I am new to Grakn as well as Java. Can you please provide a document which helps novice like us to run the Java code for Text mining in grakn. Or Can the same be implemented in Python }
Request to provide a step by step instructions.

Make the initial setup of UQ scripts easier, by inputting various paths and parameters using SCIRun first. This could even run a few examples of what the toolkit can do as well.

Hi @damaggu - could you please use the NumPy docstring style for docstrings?
This will make the docstrings more transparent to people working with the scientific python stack, and we already have some experience with troubleshooting Sphinx docs generation from this format.

https://github.com/IBT-FMI/SAMRI/blob/2ebfe09

Example folder with json documents to be enriched. This could be also used for tests.

Moreover, add a setting example in Wiki and any other information