A solution is presented for combining Natural Language Processing (NLP) with knowledge graphs to extract valuable insights from relevant articles automatically. The proposed approach uses Diffbot's APIs to retrieve articles related to cryptocurrencies, translates foreign articles using Google Translate API, and imports them into Neo4j. NLP models are then used to extract entities and relationships from the text, which are stored in Neo4j for graph analysis. Various applications can be developed using this data pipeline, such as monitoring news about companies or competitors, predicting future events like acquisitions, and fueling machine learning models for desired use cases like predicting crypto trends. The code is available on GitHub, and the solution has been applied to a sample dataset of articles related to cryptocurrencies, resulting in valuable insights into entities, relationships, and sentiment analysis.