  Cyber Threat Intelligence (CTI) is information describing threat vectors,
vulnerabilities, and attacks and is often used as training data for AI-based
cyber defense systems such as Cybersecurity Knowledge Graphs (CKG). There is a
strong need to develop community-accessible datasets to train existing AI-based
cybersecurity pipelines to efficiently and accurately extract meaningful
insights from CTI. We have created an initial unstructured CTI corpus from a
variety of open sources that we are using to train and test cybersecurity
entity models using the spaCy framework and exploring self-learning methods to
automatically recognize cybersecurity entities. We also describe methods to
apply cybersecurity domain entity linking with existing world knowledge from
Wikidata. Our future work will survey and test spaCy NLP tools and create
methods for continuous integration of new information extracted from text.
