/kcap17-tutorial

Material for tutorial "Hybrid techniques for knowledge-based NLP: Knowledge graphs meet machine learning and all their friends" at KCAP 2017, Austin (Texas)

Primary LanguageJupyter Notebook

KCAP 2017 Tutorial: NLP and Knowledge-based methods with spaCy

Material for tutorial @KCAP 2017 "Hybrid techniques for knowledge-based NLP: Knowledge graphs meet machine learning and all their friends"

Pre-requisites

  1. This tutorial uses Python 3 and Jupyter Notebooks, which you can install via pip or Anaconda (http://jupyter.readthedocs.io/en/latest/install.html)

  2. Install spaCy for your platform using the nice web helper at: https://spacy.io/usage/#section-quickstart

Contents

  • Get started with spaCy notebook provides a quick intro to spaCy
  • Writing custom components and Entity Linking with spaCy notebook provides an intro to custom components and uses a small library for Entity Linking with spaCy and AGDISTIS (https://github.com/dice-group/AGDISTIS.)
  • lib Contains a small library for entity linking with spaCy