h. Add to the set of query names all pairs of “first names + last names” produced by combining the sets of first and last names. i. This procedure is carried for every raw name variant. l1.7.A.6 — Find the word match frequencies of all names. Given the set of names which may refer to an individual, we wish to find the time resolved words frequencies of these names. The frequency of the name, which corresponds to a measure of how often an individual is mentioned, provides a metric for the fame of that person. We append the word frequencies of all the names which can potentially refer to an individual. This enables us, in a later step, to identify which name is the relevant. 6) Append the fame signal for each query name of each record. The fame signal is the timeseries of normalized word matches in the complete English database. l1.7.A.7 — Find ambiguous names which can refer to multiple individuals. Certain names are particularly popular and are shared by multiple people. This results in ambiguity, as the same query name may refer to a plurality of individuals. Homonimity conflicts occur between a group of individuals when they share some part of, or all, their name. When these homonimity conflicts arise, the word frequency of a specific name may not reflect the number of references to a unique person, but to that of an entire group. As such, the word frequency does not constitute a clear means of tracking the fame of the concerned individuals. We identify homonimity conflicts by finding instances of individuals whose names contain complete or partial matches. These conflicts are, when possible, resolved on the basis of the importance of the conflicted individuals in the following step. Typical homonimity conflicts are shown in Table $11. 7) Identify homonimity conflicts. Homonimity conflicts arise when the query names of two or more individuals contain a substring match. These conflicts are distinguished as such : a. For every query name of every record, find the se