1. A method for managing documents over a network using one or more processors that execute instructions to perform actions, comprising: instantiating a document engine to identify one or more clauses of natural language words in a document, wherein the document is associated with one or more document types, and wherein the one or more clauses are included in a data object as one or more self-referential records to improve the performance of computing resources employed to execute the instructions; and instantiating a validation engine to perform actions, including: providing one or more evaluations for the one or more clauses based on one or more evaluators and one or more machine learning (ML) models, wherein the one or more evaluations are employed to assign each of the clauses to one of a plurality of categories, and wherein each of the one or more clauses is associated with a confidence score based on the one or more evaluations; providing one or more semantic evaluators based on the one or more document types; assigning the category and the confidence score to the one or more clauses based on the one or more evaluations performed by one or more of textual evaluators or the semantic evaluators; determining the one or more ML models based on the category assigned to the one or more clauses; classifying the one or more clauses based on the one or more ML models; employing a result of the classification to modify the confidence score associated with the one or more clauses; monitoring one or more actions associated with the one or more clauses, wherein the one or more actions include one or more updates to content of the one or more clauses; and identifying one or more inconsistent evaluations, wherein the inconsistent evaluations identify the one or more clauses that have a confidence score that exceeds a pre-determined high threshold value and also a quantity of content updates that exceeds another pre-determined high threshold value; and instantiating a machine learning (ML) engine to perform actions including: retraining a portion of the one or more ML models based on the updated content of the one or more clauses associated with the inconsistent evaluations, wherein the retrained portion of the one or more ML models increases one or more confidence scores associated with each of the one or more clauses that already include content that is equivalent to the content updates of the one or more clauses associated with the inconsistent evaluations, and wherein the retrained portion of the one or more ML models decreases one or more confidence scores associated with the one or more clauses associated with the one or more inconsistent evaluations.