11. The non-transitory computer-readable medium of claim 10 , wherein the first entity comprises a plurality of entities referenced in the document and the multimedia asset comprises a plurality of multimedia assets; wherein associating the first entity with the multimedia asset comprises associating each of the plurality of entities with a respective one of the plurality of multimedia assets; further comprising: program code for identifying, for each of the plurality of entities, a respective portion of the document referencing the first entity; and program code for generating a navigation interface comprising the multimedia assets associated with the plurality of entities, wherein each of the multimedia assets included in the navigation interface is configured to receive input representing a command to navigate to a respective portion of the document referencing a respective entity associated with the multimedia asset.
10. A non-transitory computer-readable medium embodying program code executable by a processing device, the non-transitory computer-readable medium comprising: program code for identifying a first entity referenced in a document, wherein the first entity is identified using a first word or phrase located in a first portion of the document and having a first root word, wherein identifying the first entity comprises: identifying an n-gram in the document corresponding to the first entity, wherein identifying the n-gram comprises: converting text in the document to a root form of the text by performing at least one of (i) converting a plural form of the text to a singular form of the text or (ii) converting a possessive version of the text to a non-possessive version of the text, removing, from the text, at least one of (i) an article or (ii) a preposition, splitting the text into token elements, and applying, to the text, at least one of segmentation, n-gram extraction, or part-of-speech tagging, accessing a feature ontology, wherein the feature ontology comprises a mapping between a plurality of entities identified as n-grams and a plurality of classifications for the entities, wherein the feature ontology includes a character class that maps character entities to corresponding character references in the document, a setting class that maps setting entities to corresponding setting references in the document, and an emotion class that maps emotion entities to corresponding emotion reference in the document, and modifying the feature ontology to include the n-gram corresponding to the first entity; program code for associating the first entity with a multimedia asset; program code for determining that a second word or phrase in a second portion of the document refers to the first entity, wherein the second word or phrase includes a second root word—that is different from the first root word in the first word or phrase; program code for generating a layout for the second portion of the document based on determining that the second word or phrase refers to the first entity, wherein the layout includes the multimedia asset associated with the first entity; and program code for rendering the layout with the second portion for display.