Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for temporal modeling. One of the methods includes for each of one or more candidate anchors included in a plurality of tokens for a document, the plurality of tokens including a) at least one temporal modifier with a span, and b) at least one anchor i) for the temporal modifier and ii) that has a duration at least partially included in the span of the temporal modifier: accessing a representation of a context for the corresponding candidate anchor in the document; determining an attention of the corresponding token on the corresponding candidate anchor; and determining whether a duration of the corresponding candidate anchor is likely included in the span of the temporal modifier; and storing, in memory, data for the document that indicates that the corresponding candidate anchor is an anchor for the temporal modifier.

Abstract: Among other things, unstructured text items are processed to identify elements of the unstructured text items relevant to classification rules of quality metrics applicable to services provided by a healthcare provider with respect to diseases, conditions, or interventions of patients. The classification rules define classifications of patients based on diseases, conditions, or interventions of patients or on aspects of the services provided. Through a user interface, the unstructured text items, the identified elements, and user interface controls for classifying the patients with respect to the classification rules, based on the identified elements, are presented to the user.

Abstract: Among other things, unstructured text items are processed to identify elements of the unstructured text items relevant to classification rules of quality metrics applicable to services provided by a healthcare provider with respect to diseases, conditions, or interventions of patients. The classification rules define classifications of patients based on diseases, conditions, or interventions of patients or on aspects of the services provided. Through a user interface, the unstructured text items, the identified elements, and user interface controls for classifying the patients with respect to the classification rules, based on the identified elements, are presented to the user.

Abstract: Among other things, unstructured text items are processed to identify elements of the unstructured text items relevant to classification rules of quality metrics applicable to services provided by a healthcare provider with respect to diseases, conditions, or interventions of patients. The classification rules define classifications of patients based on diseases, conditions, or interventions of patients or on aspects of the services provided. Through a user interface, the unstructured text items, the identified elements, and user interface controls for classifying the patients with respect to the classification rules, based on the identified elements, are presented to the user.

Abstract: Among other things, unstructured text items are processed to identify elements of the unstructured text items relevant to classification rules of quality metrics applicable to services provided by a healthcare provider with respect to diseases, conditions, or interventions of patients. The classification rules define classifications of patients based on diseases, conditions, or interventions of patients or on aspects of the services provided. Through a user interface, the unstructured text items, the identified elements, and user interface controls for classifying the patients with respect to the classification rules, based on the identified elements, are presented to the user.