The growing volume of electronically available text provides the opportunity to extract potentially relevant information that may offer valuable insights. To this end, the cataloguing of documents based on named entity mentions is an essential task. Development of text mining approaches for extracting entities and relationships may enable efficient management and retrieval of relevant information ... [Show full abstract] within specific contexts. The system described here, ChemGrab, focused on the BioCreative V.5 CEMP Challenge that aims to identify mentions of chemical entities from within patent text. The approach used in this study to identify chemical mentions used a combination of a negativedictionary and rules based on word-level features. The system performance on the test set achieved a micro precision, recall, and F-score of 0.53, 0.67, and 0.59, respectively.