1. Predictive natural language processing models

    Features are disclosed for updating or generating natural language processing models based on information associated with items expected to be referenced in natural language processing input, such as audio of user utterances, user-entered text, etc. Natural language processing models may include, e.g., language models, acoustic models, named entity recognition models, intent classification models, and the like. The models may be updated or generated based on selected features of input data and a machine learning model trained to produce probabilities based on the selected features.

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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD