9. A computer-implemented method performed by a data processing apparatus, the method comprising: generating a trained natural language processing model based on receiving natural language training on a training data set, wherein the training data set comprises a plurality of training examples, each training example comprising text, natural language processing tags, and information retrieval model annotations, the information retrieval model annotations being generated by an information retrieval model; wherein receiving natural language training on the training data set comprises: extracting information retrieval features from one of the training examples in the training data set based on the information retrieval model annotations, predicting a part-of-speech tag for at least one word in the training example, generating a confidence score for the predicted part-of-speech tag, and filtering the predicted part-of-speech tag if the confidence score is below a threshold; receiving a target document comprising text and at least one information retrieval model annotation, the at least one information retrieval model annotation being generated by the information retrieval model; generating a prediction and an additional confidence score for the prediction for at least one word in the text of the target document, wherein generating the prediction and the additional confidence score for the prediction comprises applying the text of the target document and the information retrieval model annotation to the trained natural language processing model to generate the prediction; and using the prediction in performing one or more further actions relevant to the target document.
9. A computer-implemented method performed by a data processing apparatus, the method comprising: generating a trained natural language processing model based on receiving natural language training on a training data set, wherein the training data set comprises a plurality of training examples, each training example comprising text, natural language processing tags, and information retrieval model annotations, the information retrieval model annotations being generated by an information retrieval model; wherein receiving natural language training on the training data set comprises: extracting information retrieval features from one of the training examples in the training data set based on the information retrieval model annotations, predicting a part-of-speech tag for at least one word in the training example, generating a confidence score for the predicted part-of-speech tag, and filtering the predicted part-of-speech tag if the confidence score is below a threshold; receiving a target document comprising text and at least one information retrieval model annotation, the at least one information retrieval model annotation being generated by the information retrieval model; generating a prediction and an additional confidence score for the prediction for at least one word in the text of the target document, wherein generating the prediction and the additional confidence score for the prediction comprises applying the text of the target document and the information retrieval model annotation to the trained natural language processing model to generate the prediction; and using the prediction in performing one or more further actions relevant to the target document. 10. The computer-implemented method of claim 9 , wherein the target document is one of a search query and a potential search result.