This paper describes a series of experiments in using logistic regression machine learning as a method for entity resolution. From these experiments the authors concluded that when a supervised ML algorithm is trained to classify a pair of entity references as linked or not linked pair, the evaluation of the model’s performance should take into account the transitive closure of its pairwise lin...

• Semantic knowledge strongly influences working memory performance. relatedness impacts performance during encoding. There is no evidence that semantic contributes to recall. via activated long-term memory. The ability store information in verbal (WM) closely interacts with our linguistic knowledge. For instance, we can hold semantically related words (e.g., “cat, dog, bird”) better WM than un...