Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for natural language processing. One of the methods includes the steps of receiving a first set of labeled data from a first data source; receiving a text string from a second data source; performing natural language processing on the text string to extract particular text portions and generate a second set of labeled data; performing a comparison between the first set of labeled data and the second set of labeled data; and generating an output based on the comparison.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine learning. One of the methods includes receiving an image; providing the image to a neural network model, wherein the neural network model is trained to output predictions of one or more locations within the image and corresponding classifications; extracting text content within one or more of the one or more locations; analyzing the extracted text content using the corresponding classifications to evaluate one or more of external consistency with other data records or internal consistency with content from one or more of the particular locations; and generating one or more outputs based on the analyzing.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and applying a machine learning model. One of the methods includes the actions of obtaining a plurality of data points associated with a parcel of real property; using a machine learning model to generate a prediction from the obtained plurality of data points, the prediction indicating a likelihood that the real property will satisfy a particular parameter, wherein the machine learning model is trained using a training set comprising a collection of data points associated with a labeled set of real property parcels distinct from the specified parcel of real property, the label indicating the particular parameter and corresponding value for each real property parcel of the training set; and based on the prediction, classifying the specified parcel of real property according to a determination of whether the predicted value of the parameter satisfies a threshold.

Abstract: Provided is a method including obtaining a first data object including a first set of data entries, wherein each data entry of the first set of data entries includes text content associated with a time entry. The method includes generating a first data object score using the text content and the time entries included in the first set of data entries and using scoring parameters, determine that the first data object score satisfies a data object score condition; perform in response to the first data object score satisfying the data object score condition, a condition-specific action associated with the data object score condition.