1. A system for generating annotations of a document, comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for implementing the following functionality: a plurality of neurons organized as a bidirectional neural network, the neurons being associated with words (word-neurons), and sentences (sentence-neurons), and the sentences being extracted from documents, wherein the word-neurons are organized into a first layer and the sentence-neurons are organized into a second layer, the first layer being a layer into which the input query is inputted, wherein at least some of the word-neurons of the first layer have connections between each other, and wherein the word-neurons include additional words, different from the search query, generated by the neural network from the sentences; (a) an activity regulator that regulates a sum of all activity of all active neurons of the neural network that are excited at any given time; and (b) in response to a user interactively changing a context of an input query, means for displaying sentences corresponding to the sentence-neurons to a user and identifying the sentence-neurons that correspond to sentences taken from the documents having the highest relevance to document meaning based on a predetermined percentage of document meaning, (c) wherein the predetermined percentage of document meaning is a function of percentage of meaning of the sentences; (d) wherein the percentage of meaning of each sentence, describing the degree of relevance of the sentence to the document, is calculated by the bidirectional neural network, and (e) wherein the taken sentences represent the annotations of a selected document.