An ensemble of three language models is used to predict the next token. Each model outputs a probability distribution over a small vocabulary. Based on the principle of averaging these distributions to determine the final output, which token should be selected?

Model 1: {'mat': 0.5, 'rug': 0.2, 'floor': 0.2, 'chair': 0.1} Model 2: {'mat': 0.1, 'rug': 0.6, 'floor': 0.2, 'chair': 0.1} Model 3: {'mat': 0.3, 'rug': 0.3, 'floor': 0.3, 'chair': 0.1}