1. A method, performed by computing hardware and programmable memory, for determining whether a first pinnacle concept is referenced by a first unit of natural language discourse, comprising: parsing the first unit of natural language discourse into a first parse structure that represents each sub-unit, of the first unit of natural language discourse, by a node; adding at least one concept-value pair, each of which indicates a reference to a same non-Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a first linguistic feature from a first set of linguistic features and the first set of linguistic features is approximately complete with respect to the non-Quantifier concept; adding at least one concept-value pair, each of which indicates a reference to a same Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a second linguistic feature from a second set of linguistic features and the second set of linguistic features is approximately complete with respect to the Quantifier concept; propagating the at least one concept-value pair for the Quantifier concept; identifying a first node of the first parse structure that has at least one concept-value pair for the non-Quantifier concept and at least one concept-value pair for the Quantifier concept; determining a first value to be scaled from the least one concept-value pair for the non-Quantifier concept; determining a first scaling value from the least one concept-value pair for the Quantifier concept; scaling the first value to be scaled with the first scaling value to produce a first scaled value; and propagating the at least one concept-value pair for the non-Quantifier concept.
1. A method, performed by computing hardware and programmable memory, for determining whether a first pinnacle concept is referenced by a first unit of natural language discourse, comprising: parsing the first unit of natural language discourse into a first parse structure that represents each sub-unit, of the first unit of natural language discourse, by a node; adding at least one concept-value pair, each of which indicates a reference to a same non-Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a first linguistic feature from a first set of linguistic features and the first set of linguistic features is approximately complete with respect to the non-Quantifier concept; adding at least one concept-value pair, each of which indicates a reference to a same Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a second linguistic feature from a second set of linguistic features and the second set of linguistic features is approximately complete with respect to the Quantifier concept; propagating the at least one concept-value pair for the Quantifier concept; identifying a first node of the first parse structure that has at least one concept-value pair for the non-Quantifier concept and at least one concept-value pair for the Quantifier concept; determining a first value to be scaled from the least one concept-value pair for the non-Quantifier concept; determining a first scaling value from the least one concept-value pair for the Quantifier concept; scaling the first value to be scaled with the first scaling value to produce a first scaled value; and propagating the at least one concept-value pair for the non-Quantifier concept. 23. The method of claim 1 , wherein the step of scaling further comprises: limiting the first scaled value to be less than a maximum value.