17. The computer system of claim 11 , wherein the configurably boosting comprises boosting grammar-based relevancy measures of particular grammar-based metadata based, at least in part, on a determination that the particular grammar-based metadata and particular topic-based metadata correspond to a same node of the multi-level taxonomy.
11. A computer system comprising a processor and memory, wherein the processor and memory in combination are operable to perform a method comprising: receiving input text over a computer network; projecting, using a vector inference engine of the computer system, the input text on a vector space defined by a pre-trained model, the pre-trained model comprising vectors that have been annotated with topics of a multi-level taxonomy, the vector inference engine having been trained via the pre-trained model, the projecting yielding an inferred vector; identifying vectors of the pre-trained model that are deemed sufficiently similar to the inferred vector; accessing, from the pre-trained model, in-memory pre-associated topics of the identified vectors; processing the in-memory pre-associated topics, the processing the in-memory pre-associated topics yielding a de-duplicated topic list in relation to topic-relevancy measures; querying a descriptor data store for in-memory pre-associated metadata descriptors of the de-duplicated topic list, wherein the in-memory pre-associated metadata descriptors correspond to nodes of the multi-level taxonomy; processing the in-memory pre-associated metadata descriptors, the processing the in-memory pre-associated metadata descriptors yielding a de-duplicated topic-based descriptor list in relation to topic-based descriptor-relevancy measures; automatically determining parts of speech of tokens of the input text; searching a metadata store using the tokens and the parts of speech, the metadata store comprising a part-of-speech tagged version of the multi-level taxonomy, the searching comprising identifying, at a first level and a second level of the multi-level taxonomy, nodes that include metadata which sufficiently match the tokens and the parts of speech of the tokens, wherein the searching yields best-match grammar-based metadata descriptors, wherein the best-match grammar-based metadata descriptors correspond to nodes of the multi-level taxonomy; processing the best-match grammar-based metadata descriptors, the processing the best-match grammar-based metadata descriptors yielding a de-duplicated grammar-based descriptor list in relation to grammar-based descriptor-relevancy measures; analyzing, relative to the multi-level taxonomy, hierarchical relationships between the de-duplicated grammar-based descriptor list and the de-duplicated topic-based descriptor list; configurably boosting at least a portion of the grammar-based descriptor-relevancy measures responsive to the analyzing; and storing the de-duplicated topic-based descriptor list, the topic-based descriptor-relevancy measures, the de-duplicated grammar-based descriptor list and the grammar-based descriptor-relevancy measures in relation to the input text.