1. A computer-implemented method performed by a data processing apparatus, the method comprising: obtaining a training data set comprising at least one training example, the at least one training example being annotated with at least one training example natural language processing tag; adding a training example information retrieval model annotation to the at least one training example in the training data set to obtain an annotated training data set; training a natural language processing model on the annotated training data set to obtain a trained natural language processing model, wherein training comprises training the natural language processing model based on both the training example natural language processing tag and the training example information retrieval model annotation of the at least one training example, and wherein training the natural language processing model further comprises: generating a part-of-speech tag for at least one word in the at least one training example, generating a confidence score for the part-of-speech tag, and filtering out the part-of-speech tag if the confidence score for the part-of-speech tag is below a threshold; receiving a search query or a potential search result; adding an information retrieval model annotation to the search query or the potential search result; applying the trained natural language processing model to the search query or the potential search result to obtain a prediction, wherein applying the trained natural language processing model to obtain the prediction comprises using the information retrieval model annotation added to the search query or the potential search result; and using the prediction to retrieve information relevant to the search query or to determine relevance of the potential search result.